Abstract
Importance
Cerebral microbleeds are hypothesized downstream markers of brain damage caused by both vascular and amyloid pathological mechanisms. To date, it remains unclear whether their presence if associated with cognitive deterioration in the general population.
Objective
To determine whether microbleeds, and more specifically microbleed count and location, associate with an increased risk of cognitive impairment and dementia in the general population.
Design
Prospective population-based Rotterdam Study.
Setting
General community.
Participants
In the Rotterdam Study, we assessed presence, number, and location of microbleeds at baseline (2005–2011) on brain MRI of 4,841 participants aged ≥45 years. Participants underwent neuropsychological testing at two time points on average 5.9 years (SD 0.6) apart, and were followed for incident dementia throughout the study period until 2013. The association of microbleeds with cognitive decline and dementia was studied using multiple linear regression, linear mixed effects modeling, and Cox proportional hazards.
Exposure
cerebral microbleed presence, location, and number.
Main outcomes
cognitive decline and dementia.
Results
Microbleed prevalence was 15.3% (median count 1 [1–88]). Presence of >4 microbleeds associated with cognitive decline. Lobar (with or without cerebellar) microbleeds were associated with decline in executive functions, information processing, and memory function, whereas microbleeds in other brain regions were associated with decline in information processing and motor speed. After mean follow-up of 4.8 years (SD 1.4), 72 people developed dementia, of whom 53 had Alzheimer’s disease. Presence of microbleeds was associated with an increased risk of dementia (age, sex, education adjusted HR 2.02, 95%CI 1.25;3.24), including Alzheimer’s dementia (HR 2.10, 95%CI 1.21;3.64).
Conclusions and relevance
In the general population, a high microbleed count associated with an increased risk of cognitive deterioration and dementia. Microbleeds thus mark the presence of diffuse vascular and neurodegenerative brain damage.
Introduction
With increasing life expectancy, societies are facing a major public health challenge as the number of people living with cognitive impairments and dementia are growing steadily. There is a growing need to identify early etiological markers of cognitive impairment and dementia, since timely implementation of preventive strategies is key to positively influence the disease course. Accumulating evidence suggests that vascular pathology has a central role in cognitive deterioration.1 Studies that have investigated pathological changes of cerebral small vessels emphasized a potential role for these vessels in the pathogenesis of cognitive impairment and dementia.2–4 Arteriosclerosis and amyloid angiopathy are leading causes of cerebral small vessel disease. Consequences of small vessel disease on brain parenchyma can be visualized by neuroimaging. These lesions can either be ischemic (lacunes, white matter lesions) or hemorrhagic (cerebral microbleeds). While the underlying pathogenic cascade of lacunes and white matter lesions mainly revolves around vascular risk factors (i.e., chronic hypertension, smoking, diabetes),5 microbleed pathogenesis involves vessel wall damage due to both vascular risk factors and accumulation of beta-amyloid.6 As such, it has been suggested that microbleeds may help explain the overlap between cerebrovascular and neurodegenerative pathology in cognitive dysfunction and dementia.
While microbleeds do not appear to affect the rate of cognitive decline in patients with Alzheimer’s disease,7 it remains unclear whether microbleeds play a role in cognitive deterioration in non-cognitively impaired individuals. This is mainly due to the lack of longitudinal data and the heterogeneity of cognitive tests used in previous studies. Thus far, cross-sectional studies in the general population showed that a high microbleed count associated with lower scores on MMSE and on tests sensitive to executive function, processing speed, and motor function.8–11 Studies in patients with cerebrovascular disease report inconsistent results, with some reporting only associations between microbleeds and global cognition, and others also between microbleeds and specific cognitive domains.12–15 To date, it also remains unclear whether community-dwelling elderly with microbleeds are at increased risk of dementia, and more particularly Alzheimer’s disease. Should microbleeds relate to Alzheimer’s dementia, it would highlight the role of vascular pathology in the etiology of the disease and build a bridge between the vascular and amyloid hypothesis.
In the prospective population-based Rotterdam Study, we studied whether presence, number and location of microbleeds marks decline of cognitive functioning, and associates with an increased risk of dementia.
Methods
Study population
This study was conducted in the prospective population-based Rotterdam Study.16 After its start in 1990, a total of 7,983 people were included in the initial study wave. In 1999, the cohort was expanded with 3,011 participants, and in 2006 again with 3,932 participants. The total of 14,926 participants enrolled, were invited to undergo home interviews and various physical and laboratory examination at the research center every 4 years. Of these, 5,074 (88.5% of invitees) non-demented participants without MRI contra-indication underwent brain MRI between 2005 and 2011 (considered as baseline for this study) for the assessment of microbleeds.17 We excluded participants if scans were incomplete or of inadequate quality (n=129). In addition, we excluded 56 participants with insufficient screening for dementia, and 48 participants for whom follow-up for incident dementia ended before date of MRI due to the absence of automatic linkage between the general practitioners office and our study database. In total, 4,841 participants were included in the dementia analysis. Of these, 3,257 participants (without prevalent or incident dementia) underwent both baseline and follow-up cognitive testing, and were included in the analysis of cognitive decline. Baseline cognition was assessed during the research visit closest to MRI date (2002–2008) and reassessed at a subsequent visit (2009–2014). Follow-up cognitive tests were unavailable for participants who underwent baseline brain MRI between 2009 and 2011. The Rotterdam Study has been approved by the Medical Ethics Committee of the Erasmus MC and by the Ministry of Health, Welfare and Sport of the Netherlands, implementing the “Wet Bevolkingsonderzoek: ERGO (Population Studies Act: Rotterdam Study)”. All participants provided written informed consent to participate in the study and to obtain information from their treating physicians.
Brain MRI and markers of small vessel disease
Participants were scanned on a 1.5-T MRI scanner (GE Healthcare Milwaukee, WI) using a multisequence protocol consistent of T1-weighted, proton density weighted, fluid-attenuated inversion recovery (FLAIR), and T2*-weighted sequences.17 Trained research physicians, blinded to clinical data, reviewed the MR images. Cerebral microbleeds were defined as small, round to ovoid areas of focal signal loss on T2*-weighted images. Intra-observer (k=0.87) and inter-observer agreement (k=0.85) were good.6 Microbleeds were classified manually as lobar microbleeds with or without cerebellar microbleeds (suggestive of cerebral amyloid angiopathy), and deep or infratentorial microbleeds with or without lobar microbleeds (suggestive of hypertensive arteriopathy). In addition, we classified every microbleed according to its topographic distribution in the brain (frontal, temporal, parietal, and occipital lobe, infratentorial, and deep). The topographic categorization of microbleeds was done semi-automatically, as described previously.18 In short, after microbleeds were manually labeled, automated lobe segmentation was done by nonrigid registration of 6 manually annotated lobe atlases to the participant under investigation using the Elastix software. Lobe segmentations were combined with the manually labeled microbleeds, to determine the lobar distribution of microbleeds. Infarcts were defined as focal lesions with the same signal intensity as cerebrospinal fluid on all sequences. Infarcts ≥3 and <15mm in size were classified as lacunes, infarcts ≥15 mm as subcortical infarcts, and infarcts involving cortical gray matter as cortical infarcts. Brain tissue was segmented into gray matter, white matter, and cerebrospinal fluid using automated post-processing tools that included conventional k-nearest-neighbor brain tissue classifier extended with white matter lesion segmentation.19 Intracranial volume was defined the sum of cerebrospinal fluid, gray matter white matter, and white matter lesion.
Assessment of cognitive functioning
The neuropsychological test battery comprised the Mini-Mental State Examination (MMSE), letter-digit-substitution task (LDST), word fluency test (WFT), Stroop test (consisting of reading, color-naming, and interference subtask), 15-word verbal learning test (15-WLT) and Purdue Pegboard test.20 We computed compound scores for global cognition (average Z-score of the Stroop interference subtask, LDST, WFT, delayed recall of the 15-WLT, and Purdue Pegboard), executive functioning (average Z-score of Stroop interference subtask, LDST, WFT), information-processing speed (average Z-score of Stroop reading and color-naming subtask, and LDST), memory (average Z-score of immediate and delayed recall of the 15-WLT), and motor speed (average Z-score of Purdue Pegboard).
Assessment of dementia
A three-step protocol was used to screen for prevalent and incident dementia. All participants underwent the MMSE and the Geriatric Mental Schedule (GMS) organic level. Those who screened positive on either test, MMSE <26 or GMS organic level >0, also underwent an examination and informant interview with the Cambridge Examination for Mental Disorders in the Elderly. Those allegedly suffering from dementia underwent further neuropsychological testing if necessary. In addition, all participants were continuously monitored for dementia by linking the study database to digitized medical records from general practitioners and the Regional Institute for Outpatient Mental Health Care. If available, clinical neuroimages were used in the diagnostic process. The final diagnosis was made in accordance with international criteria and determined by a consensus panel led by a neurologist.21,22 Follow-up for incident dementia was complete until January 1st, 2013, for 23177 (98.5%) of potential person-years.
Assessment of covariates
Covariates were assessed during the same visit in which baseline cognition was tested. Blood pressure was measured in two readings using a random zero sphygmomanometer in sitting position, and both measures were averaged. Hypertension was defined as a systolic blood pressure of ≥140 mmHg, or diastolic blood pressure of ≥90 mmHg, or the use of blood pressure-lowering medication. Serum total and high-density lipoprotein cholesterol were measured using an automated enzymatic procedure. Smoking behavior was classified as “ever” versus “never” smoked. People were considered diabetic when fasting blood glucose levels were ≥7.0 mmol/L or when they used glucose-lowering medication. Medication use (glucose-lowering, blood pressure-lowering, and lipid-lowering medication) and education level was assessed during home visits by standardized interviews. APOE genotyping was performed on coded genomic DNA samples. Distribution of APOE genotype and allele frequencies in this population were in Hardy–Weinberg equilibrium.
Statistical analysis
We investigated the association of microbleed presence, location, and number (a priori defined categories of 1, 2–4, >4 microbleeds) with cognitive decline and dementia, using people without microbleeds as a reference group.
We first used multiple linear regression to investigate the association of microbleeds with cognitive decline. We examined microbleeds in relation to individual neuropsychological tests and afterwards with specific cognitive domains. Z-scores of baseline and follow-up cognitive tests were calculated for each participant. Decline in cognitive scores was studied by using cognitive scores at follow-up as dependent variable and adjusting for baseline test scores in the linear regression models.
Second, we used linear mixed models with added random effects to determine the relationship between microbleed count per topographic distribution in the brain and cognitive decline in specific domains.
Third, Cox proportional hazards were used to study the relation between microbleeds and dementia, including Alzheimer’s dementia. These analyses were also censored for stroke.
All analyses were adjusted for age, sex, and education. Additionally, regression models were adjusted for APOE ε4, a propensity score of cardiovascular risk (hypertension, total and HDL cholesterol, smoking status, diabetes mellitus, lipid-lowering and antithrombotic medication use), intracranial volume and other imaging markers of cerebral small vessel disease (lacunes and white matter lesions). Lacunes were modeled dichotomously. White matter lesions load was naturally transformed because of its skewed distribution and modeled continuously. Missing covariate data (≤7.0%) were imputed based on age, sex, and cardiovascular risk factors using regression models. Afterwards, logistic regression was used to compute propensity scores for cardiovascular risk. Here, microbleed status (yes versus no) was defined the dependent variable and the above-mentioned cardiovascular risk factors were considered independent covariates. The estimated propensity score was the derived predicted value of the equation. Finally, we also investigated whether adjustments for age-squared would give a better adjustment for confounding by age.
Participants with unreliable segmentations of white matter lesions volume (n=127) were excluded in the analysis involving white matter lesion volume.
Results
Microbleeds and cognitive decline
In total, 3,257 participants (mean age 59.6 years (SD 7.8), 54.7% women) without prevalent or incident dementia underwent baseline and repeat cognitive testing on average 5.9 years apart (Table 1). The prevalence of lobar microbleeds (with or without cerebellar microbleeds) and deep or infratentorial microbleeds (with or without lobar microbleeds) was respectively 10.9% and 3.8%. The topographic distribution of cerebral microbleeds was as follows: 5.3 % had at least 1 microbleeds in frontal lobe, 5.5% in temporal lobe, 5.1% in parietal lobe, 3.4% in occipital lobe, 3.2% in infratentorial regions, and 3.5% in deep hemispheric regions.
Table 1.
Characteristics of the study population
| Cognitive decline analysis N=3,257 |
Incident dementia analysis N=4,841 |
|||
|---|---|---|---|---|
|
| ||||
| Microbleeds absent n=2,780 |
Microbleeds present n=477 |
Microbleeds absent n=3,911 |
Microbleeds absent n=930 |
|
|
| ||||
| Age, years | 59.0 (7.6) | 62.8 (8.5) | 62.4 (10.4) | 69.8 (71.7) |
| Women | 1530 (55.0) | 252 (52.8) | 2171 (55.5) | 492 (52.9) |
| Education level | ||||
| Primary education | 207 (7.4) | 37 (7.8) | 339 (8.7) | 97 (10.4) |
| Lower/intermediate general education | 995 (35.8) | 193 (40.9) | 1431 (36.6) | 361 (38.8) |
| Intermediate vocational education | 828 (29.8) | 132 (28.0) | 1180 (30.2) | 280 (30.1) |
| Higher vocational education | 728 (26.2) | 110 (23.1) | 930 (23.8) | 185 (19.9) |
| Hypertension | 1446 (52.0) | 297 (62.3) | 2304 (58.9) | 678 (72.9) |
| Total cholesterol, mmol/L | 5.6 (1.0) | 5.6 (1.1) | 5.6 (1.0) | 5.4 (1.1) |
| High-density lipoprotein cholesterol, mmol/L | 1.4 (0.4) | 1.4 (0.4) | 1.4 (0.4) | 1.4 (0.4) |
| Smoking | 1900 (68.3) | 351 (73.6) | 2706 (69.2) | 678 (72.9) |
| Diabetes mellitus | 210 (7.6) | 37 (7.8) | 330 (8.4) | 98 (10.5) |
| APOE ε4 carriers | 735 (28.2) | 141 (31.4) | 884 (28.6) | 233 (32.0) |
| Lipid-lowering medication | 585 (21.0) | 108 (22.6) | 900 (23.0) | 287 (30.9) |
| Antithrombotic medication | 511 (18.4) | 152 (31.9) | 945 (24.2) | 425 (45.7) |
| Lacunes | 103 (3.7) | 46 (9.6) | 213 (5.4) | 143 (15.4) |
| Intracranial volume, ml | 1126.4 (120.4) | 1126.8 (116.8) | 1123.6 (121.8) | 1127.6 (119.2) |
| White matter lesions volume, ml (median [IQR])* | 2.2 (1.4–3.8) | 3.1 (1.8–5.9) | 2.6 (1.5–4.9) | 5.0 (2.4–11.9) |
Values represent mean (standard deviation) for continuous variables and number (percentage) for categorical variables. The following variables had missing values: education level (n=27), hypertension (n=22), total cholesterol (n=29), HDL cholesterol (n=31), smoking (n=13), diabetes mellitus (n=51), APOE genotype (n=202), lipid-lowering medication (n=27).
Calculated in 3,130 participants with reliable white matter lesion volume segmentations.
Compared with no microbleeds, the presence of any microbleeds did not associate with decline in cognition. We did, however, observe that the presence of more than 4 microbleeds was associated with worse performance on LDST, WFT, Stroop reading and naming, immediate WLT, and Purdue Pegboard neuropsychological testing during follow-up. Furthermore, presence of multiple lobar microbleeds specifically associated with worse performance on WFT, Stroop reading and naming, and immediate WLT. Presence of multiple deep or infratentorial microbleeds associated with worse performance on Purdue Pegboard (Table 2). In accordance, lobar microbleeds were the strongest determinant for decline in information processing speed, whereas deep or infratentorial microbleeds were most strongly associated with decline in motor speed (Figure). Adjusting for APOE ε4 and cardiovascular risk factors weakened the associations of lobar microbleeds with various cognitive domains. Additionally, the association between deep or infratentorial microbleeds and information processing speed was no longer significant. Lobar microbleeds associated with decline in executive functioning and information processing speed even after correcting for other imaging markers of cerebral small vessel disease (Table 3). The additional adjustment for age-squared did not change any of the results.
Table 2.
Cerebral microbleeds and cognitive decline
| Number of participants |
LDST | WFT | Stroop reading | Stroop naming | Stroop interference | WLT immediate | WLT delayed | WLT recognition | Purdue Pegboard | |
|---|---|---|---|---|---|---|---|---|---|---|
|
|
||||||||||
| No microbleeds | 2780 | Reference | Reference | Reference | Reference | Reference | Reference | Reference | Reference | Reference |
| Microbleed, any | 477 | −0.05 (−0.12;0.02) | 0.02 (−0.06;0.11) | 0.01 (−0.08;010) | −0.03 (−0.10;0.04) | −0.07 (−0.14;0.00) | −0.01 (−0.09;0.08) | 0.04 (−0.07;1.14) | 0.03 (−0.07;0.14) | −0.03 (−0.13;0.06) |
| Single | 326 | −0.02 (−0.09;0.06) | 0.04 (−0.06;0.14) | 0.06 (−0.04;0.17) | −0.02 (−0.10;0.06) | −0.07 (−0.15;0.01) | 0.0004 (−0.10;0.10) | 0.08 (−0.04;0.20) | 0.04 (−0.10;0.17) | −0.01 (−0.12;0.11) |
| 2–4 | 107 | −0.05 (−0.18;0.09) | 0.09 (−0.08;0.26) | 0.07 (−0.11;0.25) | 0.05 (−0.08;0.19) | −0.02 (−0.16;0.11) | 0.08 (−0.09;0.25) | −0.01 (−0.21;0.20) | −0.09 (−0.31;0.14) | −0.01 (−0.20;0.18) |
| >4 | 44 | −0.32 (−0.53;−0.10) | −0.35 (−0.62;−0.08) | −0.60 (−0.89;−0.31) | −0.35 (−0.57;−0.13) | −0.20 (−0.42;0.02) | −0.31 (−0.58;−0.03) | −0.20 (−0.54;0.14) | −0.13 (−0.49;0.24) | −0.33 (−0.64;−0.03) |
|
|
||||||||||
| Lobar* | 354 | −0.05 (−0.13;0.03) | 0.001 (−0.10;0.10) | −0.01 (−0.11;0.10) | −0.03 (−0.11;0.05) | −0.06 (−0.13;0.02) | −0.01 (−0.11;0.09) | 0.04 (−0.08;0.17) | 0.06 (−0.06;0.19) | −0.05 (−0.16;0.06) |
| Single | 253 | −0.02 (−0.11;0.07) | 0.03 (−0.08;0.14) | 0.05 (−0.07;0.17) | −0.05 (−0.14;0.04) | −0.08 (−0.17;0.01) | 0.02 (−0.10;0.13) | 0.10 (−0.04;0.24) | 0.09 (−0.06;0.24) | −0.03 (−0.16;0.09) |
| 2–4 | 78 | −0.07 (−0.23;0.08) | 0.05 (−0.15;0.24) | 0.03 (−0.18;0.23) | 0.07 (−0.09;0.23) | 0.04 (−0.12;0.20) | −0.01 (−0.21;0.19) | −0.06 (−0.30;0.19) | −0.16 (−0.43;0.11) | −0.11 (−0.32;0.11) |
| >4 | 23 | −0.33 (−0.62;−0.03) | −0.52 (−0.88;−0.15) | −0.87 (−1.26;−0.47) | −0.35 (−0.65;−0.05) | −0.22 (−0.52;0.08) | −0.38 (−0.76;−0.002) | −0.34 (−0.81;0.15) | −0.14 (−0.64;0.37) | −0.09 (−0.50;0.33) |
|
|
||||||||||
| Deep or infratentorial± | 123 | −0.05 (−0.17;0.08) | 0.08 (−0.08;0.23) | 0.08 (−0.09;0.24) | 0.001 (−0.13;0.13) | −0.11 (−0.23;0.01) | 0.002 (−0.16;0.16) | 0.02 (−0.16;0.20) | −0.05 (−0.23;0.14) | 0.04 (−0.14;0.21) |
| Single | 73 | 0.002 (−0.16;0.16) | 0.09 (−0.11;0.29) | 0.12 (−0.09;0.33) | 0.09 (−0.07;0.25) | −0.05 (−0.20;0.11) | −0.05 (−0.25;0.15) | −0.001 (−0.23;0.22) | −0.15 (−0.40;0.10) | 0.10 (−0.13;0.32) |
| 2–4 | 29 | 0.01 (−0.25;0.27) | 0.21 (−0.11;0.53) | 0.19 (−0.16;0.53) | 0.0004 (−0.26;0.26) | −0.23 (−0.48;0.03) | 0.31 (−0.02;0.63) | 0.14 (−0.23;0.51) | 0.12 (−0.29;0.53) | 0.26 (−0.10;0.63) |
| >4 | 21 | −0.31 (−0.63;0.01) | −0.18 (−0.57;0.22) | −0.28 (−0.71;0.14) | −0.35 (−0.66;−0.03) | −0.19 (−0.50;0.12) | −0.23 (−0.63;0.17) | −0.06 (−0.51;0.39) | −0.11 (−0.61;0.39) | −0.61 (−1.05;−0.17) |
Values represent mean differences in Z-score of various cognitive tests in those with microbleeds compared to those without microbleeds.
Values are adjusted for age, sex, education level, baseline cognitive tests score, and time between baseline and follow-up visit.
Lobar microbleeds with or without cerebellar microbleeds.
Deep or infratentorial microbleeds with or without lobar microbleeds.
Figure. Cerebral microbleeds and decline in specific cognitive domains.
The y-axis represents age, sex, education, and baseline cognition adjusted Z scores for decline in specific cognitive domains for categories of lobar and deep or infratentorial microbleed count (x-axis), compared with a reference group without cerebral microbleeds. Error bars represent 95% confidence intervals.
Table 3.
Cerebral microbleeds and decline in specific cognitive domains
| G-factor | Executive functions | Information processing | Memory | Motor Speed | |
|---|---|---|---|---|---|
|
|
|||||
| Model I | |||||
|
|
|||||
| Lobar* | −0.02 (−0.09;0.05) | −0.03(−0.10;0.04) | −0.03 (−0.10;0.04) | −0.02 (−0.11;0.08) | −0.05 (−0.16;0.06) |
| Single | 0.0003 (−0.08;0.08) | −0.02 (−0.08;0.05) | −0.001 (−0.07;0.06) | 0.01 (−0.08;0.10) | −0.03 (−0.16;0.09) |
| 2–4 CMBs | −0.01 (−0.15;0.13) | 0.02 (−0.09;0.13) | 0.01 (−0.11;0.12) | −0.02 (−0.17;0.14) | −0.11 (−0.32;0.11) |
| >4 CMBs | −0.37 (−0.65;−0.09) | −0.31 (−0.51;−0.11) | −0.44 (−0.65;−0.22) | −0.34 (−0.64;−0.03) | −0.09 (−0.50;0.33) |
|
|
|||||
| Deep or infratentorial± | −0.02 (−0.13;0.10) | −0.03 (−0.14;0.08) | 0.01 (−0.11;0.13) | 0.02 (−0.13;0.17) | 0.03 (−0.15;0.20) |
| Single CMB | 0.03 (−0.11;0.18) | 0.02 (−0.09;0.12) | 0.06 (−0.06;0.17) | −0.02 (−0.18;0.14) | 0.10 (−0.13;0.32) |
| 2–4 CMBs | 0.06 (−0.17;0.29) | −0.03 (−0.21;0.14) | 0.05 (−0.14;0.24) | 0.21 (−0.05;0.47) | 0.26 (−0.10;0.63) |
| >4 CMBs | −0.34 (−0.62;−0.05) | −0.20 (−0.41;0.02) | −0.26 (−0.50;−0.03) | −0.13 (−0.44;0.19) | −0.61 (s;1.05;s;0.17) |
|
|
|||||
| Model II | |||||
|
|
|||||
| Lobar* | −0.02 (−0.09;0.05) | −0.03 (−0.09;0.04) | −0.02 (−0.09;0.05) | −0.02 (−0.11;0.08) | −0.05 (−0.16;0.06) |
| Single | 0.002 (−0.08;0.08) | −0.01 (−0.07;0.05) | 0.001 (−0.07;0.07) | 0.01 (−0.08;0.10) | −0.03 (−0.16;0.09) |
| 2–4 CMBs | 0.002 (−0.14;0.14) | 0.03 (−0.08;0.13) | 0.02 (−0.09;0.14) | −0.02 (−0.18;0.14) | −0.10 (−0.32;0.12) |
| >4 CMBs | −0.35 (−0.62;−0.07) | −0.29 (−0.49;−0.09) | −0.41 (−0.63;−0.19) | −0.34 (−0.65;−0.04) | −0.07 (−0.49;0.35) |
|
|
|||||
| Deep or infratentorial± | −0.003 (−0.12;0.11) | −0.02 (−0.13;0.09) | 0.02 (−0.09;0.14) | 0.02 (−0.14;0.17) | 0.04 (−0.14;0.22) |
| Single CMB | 0.04 (−0.11;0.18) | 0.02 (−0.09;0.13) | 0.06 (−0.06;0.18) | −0.02 (−0.18;0.14) | 0.10 (−0.12;0.32) |
| 2–4 CMBs | 0.08 (−0.15;0.32) | −0.02 (−0.19;0.16) | 0.07 (−0.12;0.26) | 0.21 (−0.05;0.46) | 0.29 (−0.08;0.65) |
| >4 CMBs | −0.29 (−0.57;−0.002) | −0.16 (−0.37;0.06) | −0.22 (−0.45;0.02) | −0.14 (−0.45;0.18) | −0.56 (−1.00;−0.11) |
|
|
|||||
| Model III | |||||
|
|
|||||
| Lobar* | −0.02 (−0.09;0.05) | −0.03 (−0.09;0.04) | −0.01 (−0.09;0.06) | −0.02 (−0.12;0.08) | −0.05 (−0.16;0.06) |
| Single | −0.01 (−0.09;0.07) | −0.02 (−0.08;0.04) | 0.01 (−0.06;0.07) | 0.01 (−0.08;0.10) | −0.04 (−0.16;0.09) |
| 2–4 CMBs | −0.01 (−0.16;0.13) | 0.02 (−0.08;0.13) | 0.03 (−0.09;0.14) | −0.03 (−0.19;0.13) | −0.10 (−0.33;0.12) |
| >4 CMBs | −0.29 (−0.57;0.002) | −0.24 (−0.45;−0.03) | −0.40 (−0.62;−0.17) | −0.28 (−0.60;0.04) | −0.01 (−0.43;0.42) |
|
|
|||||
| Deep or infratentorial± | 0.03 (−0.09;0.15) | 0.02 (−0.10;0.13) | 0.04 (−0.08;0.16) | 0.05 (−0.11;0.21) | 0.08 (−0.10;0.27) |
| Single CMB | 0.04 (−0.11;0.18) | 0.02 (−0.09;0.13) | 0.05 (−0.07;0.17) | −0.01 (−0.17;0.15) | 0.10 (−0.12;0.32) |
| 2–4 CMBs | 0.10 (−0.14;0.33) | −0.01 (−0.18;0.17) | 0.08 (−0.12;0.27) | 0.23 (−0.03;0.49) | 0.31 (−0.05;0.67) |
| >4 CMBs | −0.13 (−0.45;0.20) | 0.006 (−0.24;0.25) | −0.17 (−0.44;0.10) | −0.05 (−0.41;0.32) | −0.48 (−0.98;0.03) |
Values represent differences in Z-score of various cognitive domains in those with microbleeds compared to those without microbleeds.
Model I: adjusted for age, sex, education level, baseline domain tests scores, and time between baseline and follow-up visit.
Model II: as Model I, additionally adjusted for APOE ε4 carriership and a propensity score of cardiovascular risk factors which included hypertension, total and HDL cholesterol, smoking status, diabetes mellitus, lipid-lowering and antithrombotic medication use.
Model III: as Model I, additionally for lacunes, intracranial volume, white matter lesion volume.
The following neuropsychological tests were included for G-factor: Stroop interference, LDST, WFT, delayed WLT, Purdue Pegboard; for executive functions: Stroop interference, LDST, WFT; for information processing: Stroop reading and naming, LDST; for memory: immediate and delayed WLT; for motor Speed: Purdue Pegboard.
Lobar microbleeds with or without cerebellar microbleeds.
Deep or infratentorial microbleeds with or without lobar microbleeds.
Regarding the topographic distribution of cerebral microbleeds, microbleeds in distinct anatomical brain regions associated non-specifically with decline in various cognitive domains (Supplementary Table 1).
Microbleeds and dementia
Follow-up for dementia was complete in 4,841 participants (50.0% women, mean age 63.8 years) (Table 1). During a mean follow-up of 4.8 years (SD 1.4), 72 participants developed dementia, of whom 53 had Alzheimer’s dementia. The presence of microbleeds, both lobar and deep or infratentorial microbleeds, was associated with an increased risk of dementia (age, sex, and education adjusted HR for dementia in people with any microbleeds 2.02, 95% CI 1.25;3.24) (Table 4). Associations remained after censoring for stroke (HR 1.70, 95% CI 1.00;2.87). Lobar and deep or infratentorial microbleeds associated with an increased risk of Alzheimer’s dementia in the same magnitude as that of non-Alzheimer’s dementia. Significance was lost after adjusting for APOE ε4 carriership and cardiovascular risk (Table 4, model II) Associations, however, remained for deep or infratentorial microbleeds, after adjusting for other imaging markers of cerebral small vessel disease (Table 4, model III).
Table 4.
Cerebral microbleeds and the risk of dementia
| Dementia | Alzheimer’s dementia | |||
|---|---|---|---|---|
|
|
|
|||
| n/N | HR (95% CI) | n/N | HR (95% CI) | |
|
|
||||
| Model I | ||||
|
|
||||
| No microbleeds | 39/3911 | Reference | 28/3911 | Reference |
| Any microbleeds | 33/930 | 2.02 (1.25–3.24) | 25/930 | 2.10 (1.21–3.64) |
| Lobar* | 21/648 | 1.81 (1.05–3.11) | 17/648 | 2.00 (1.08–3.71) |
| Deep or infratentorial± | 12/282 | 2.39 (1.23–4.61) | 8/282 | 2.15 (0.97–4.78) |
|
|
||||
| Model II | ||||
|
|
||||
| No microbleeds | 26/3088 | Reference | 18/3088 | Reference |
| Any microbleeds | 21/728 | 1.59 (0.88–2.89) | 16/728 | 1.67 (0.83–3.36) |
| Lobar* | 15/512 | 1.65 (0.86–3.17) | 11/512 | 1.66 (0.77–3.59) |
| Deep or infratentorial± | 6/216 | 1.40 (0.55–3.52) | 5/216 | 1.58 (0.56–4.45) |
|
|
||||
| Model III | ||||
|
|
||||
| No microbleeds | 36/3743 | Reference | 26/3743 | Reference |
| Any microbleeds | 28/868 | 1.73 (1.03–2.90) | 21/868 | 1.83 (1.00–3.33) |
| Lobar* | 17/603 | 1.55 (0.86–2.81) | 14/603 | 1.70 (0.87–3.32) |
| Deep or infratentorial± | 11/265 | 2.42 (1.18–4.96) | 7/265 | 2.34 (0.98–5.63) |
Values represent adjusted hazard ratios (HR) (95% confidence interval [CI]) for incident dementia in participants with microbleeds compared to those without microbleeds.
Model I: adjusted for age, sex, and education level.
Model II: as Model I, additionally adjusted for APOE ε4 carriership (versus ε3/ε3) and a propensity score of cardiovascular risk factors which included hypertension, total and HDL cholesterol, smoking status, diabetes mellitus, lipid-lowering and antithrombotic medication use.
Model III: as Model I, additionally for lacunes, intracranial volume, white matter lesion volume.
n/N= number of dementia cases/total number of participants per strata. Numbers differ for model I to III because missing values for APOE genotype in model II were not imputed, and because white matter lesion volume was calculated in 4,611 participants in model III.
Lobar microbleeds with or without cerebellar microbleeds.
Deep or infratentorial microbleeds with or without lobar microbleeds.
Discussion
In this population-based study of middle-aged and elderly people we found that a high microbleed count (i.e., >4 microbleeds) was associated with cognitive decline. Also, presence of microbleeds was associated with an increased risk of dementia.
Presence of multiple microbleeds affected cognition in all domains in our population-based study. Previous cross-sectional studies in healthy adults already demonstrated that microbleeds, especially in large numbers, are related to lower MMSE scores, worse information processing, and worse executive functioning.8–11 The only study that investigated the relationship between microbleeds and cognitive decline longitudinally was performed in patients with the genetic small vessel disease, CADASIL.23 That study found similar results for decline in global cognition, executive function, and memory, but did not investigate this separately for different microbleed locations. Cross-sectional studies in patients with or at increased risk of cerebrovascular disease reported inconsistent results on the associations of microbleeds with worse performance on global cognition, tests for executive function, tests for memory function, and tests for psychomotor speed.12–15 In addition, in memory clinic populations microbleeds associated with worse MMSE scores (as measure for global cognition) and several cognitive domains with exception of language skills.24,25 although the majority of studies were unable to demonstrate any association.26–29
Mechanisms by which microbleeds influence cognitive function remain speculative, and may either be causal or non-causal.30 Microbleeds located strategically in the brain may cause focal damage to neurological tracts leading to impairment in specific cognitive domains.14 On the other hand, microbleeds may represent a proxy measure of cerebral vascular pathology at large, and their presence may influence cognition indirectly. The latter hypothesis is supported by our findings as we found associations with multiple microbleeds in widespread areas, rather than with single or multiple microbleeds clustered in a specific brain region. In addition, microbleeds in non-strategic topographic brain regions associated with impairments in executive functioning, information processing, and memory. Also, these associations were attenuated after adjusting for white matter lesions and lacunes, indicating that these lesions have a shared effect on cognition. Indeed, previous evidence also suggest that these lesions often co-exist, share risk factors, and even that their presence indicates a single pathological continuum.31–36 Microbleeds may less likely be a sole causal determinant of cognitive deterioration but rather a downstream product of both severe vascular and neurodegenerative pathology.
Lobar microbleeds were associated with decline in distinct cognitive domains when compared with microbleeds in other locations. The association of lobar microbleeds with memory might partly be explained by the fact that multiple lobar microbleeds had a predilection for the temporal lobes in our study.37 In turn, deep or infratentorial microbleeds could strategically affect infratentorial and deep hemispheric brain regions (including basal ganglia and the internal capsule) to influence motor function. It should be noted, however, that participants with deep or infratentorial microbleeds often had a higher microbleed count and more often had mixed microbleeds (i.e., microbleeds in lobar and non-lobar brain regions). Hence, microbleed count per topographic brain regions may be more informative than the categorizations per presumed underlying vasculopathy in assessing cognitive deterioration.
Microbleeds are found in 18–32% of patients with Alzheimer’s disease,38 with most patients exhibiting a predominance for cortical-subcortical microbleeds.27 In the general population, we found that microbleeds related to an increased risk of dementia, including Alzheimer’s dementia. We found strong associations for deep or infratentorial microbleeds. Our study underscores the role of vascular pathology in the pathogenesis of dementia, including Alzheimer’s dementia. The question remains how vascular pathology interacts with amyloid pathology to cause clinical cognitive deterioration and dementia. In principle, the relationship could move in two directions: either vascular amyloid deposition adversely affects reactivity of cerebral microvasculature causing loss of function with ischemic and hemorrhagic damage, or hypertensive damage to small vessels leads to disturbances in amyloid clearance, increasing the amyloid deposits in vessel walls.38 Accumulating evidence suggests that vascular damage may be of particular importance in the initiation of neurodegenerative disease whereas the influence of b-amyloid becomes more prominent in the clinical disease stage.39,40
Strengths of our study include the longitudinal population-based design with large sample size, the use of an extensive neuropsychological test battery, and the virtually complete screening for incident dementia. Some limitations of our study also have to be mentioned. First, we applied multiple statistical tests in our study, increasing the chance of type I errors. However, correcting for multiple testing seems inappropriate since cognitive tests/domains were not independent from one another, and microbleeds in different locations are correlated. Second, selection bias may have influenced our results, as healthier people without subjective memory complains were more likely to receive follow-up cognitive testing. This would most likely have biased our results towards the null. Third, the microbleed number rated may not reflect the true biological number since microbleed detection strongly depends on technical imaging methods used. Fourth, the small number of incident dementia cases in our relatively young cohort hampered our ability to control for all potential confounders, and residual confounding may have affected our results. Specifically, residual confounding by age may have biased the associations presented in our study.
In conclusion, microbleeds are associated with cognitive decline and dementia in the general population. A high microbleed count may represent a proxy for diffuse vascular and neurodegenerative brain damage, which predisposes to progressive cognitive deterioration.
Supplementary Material
Acknowledgments
The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. Dr. Meike Vernooij received a research fellowship from the Erasmus University Medical Center, Rotterdam, the Netherlands and a ZonMW clinical fellowship (90700435).
Footnotes
Conflicts of interest
None of the authors report disclosures in relationship to this manuscript. Dr. Aad van der Lugt received a research grant from GE healthcare and he serves on the speakers’ bureau of GE Health Care.
References
- 1.Gorelick PB, Scuteri A, Black SE, et al. Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the american heart association/american stroke association. Stroke. 2011 Sep;42(9):2672–2713. doi: 10.1161/STR.0b013e3182299496. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Kalaria RN. Cerebrovascular disease and mechanisms of cognitive impairment: evidence from clinicopathological studies in humans. Stroke. 2012 Sep;43(9):2526–2534. doi: 10.1161/STROKEAHA.112.655803. [DOI] [PubMed] [Google Scholar]
- 3.Pantoni L, Simoni M. Pathophysiology of cerebral small vessels in vascular cognitive impairment. Int Psychogeriatr. 2003;15( Suppl 1):59–65. doi: 10.1017/S1041610203008974. [DOI] [PubMed] [Google Scholar]
- 4.Martinez-Ramirez S, Greenberg SM, Viswanathan A. Cerebral microbleeds: overview and implications in cognitive impairment. Alzheimers Res Ther. 2014;6(3):33. doi: 10.1186/alzrt263. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.van Dijk EJ, Prins ND, Vrooman HA, Hofman A, Koudstaal PJ, Breteler MM. Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study. Stroke. 2008 Oct;39(10):2712–2719. doi: 10.1161/STROKEAHA.107.513176. [DOI] [PubMed] [Google Scholar]
- 6.Vernooij MW, van der Lugt A, Ikram MA, et al. Prevalence and risk factors of cerebral microbleeds: the Rotterdam Scan Study. Neurology. 2008 Apr 1;70(14):1208–1214. doi: 10.1212/01.wnl.0000307750.41970.d9. [DOI] [PubMed] [Google Scholar]
- 7.van der Vlies AE, Goos JD, Barkhof F, Scheltens P, van der Flier WM. Microbleeds do not affect rate of cognitive decline in Alzheimer disease. Neurology. 2012 Aug 21;79(8):763–769. doi: 10.1212/WNL.0b013e3182661f91. [DOI] [PubMed] [Google Scholar]
- 8.Poels MM, Ikram MA, van der Lugt A, et al. Cerebral microbleeds are associated with worse cognitive function: the Rotterdam Scan Study. Neurology. 2012 Jan 31;78(5):326–333. doi: 10.1212/WNL.0b013e3182452928. [DOI] [PubMed] [Google Scholar]
- 9.Qiu C, Cotch MF, Sigurdsson S, et al. Cerebral microbleeds, retinopathy, and dementia: the AGES-Reykjavik Study. Neurology. 2010 Dec 14;75(24):2221–2228. doi: 10.1212/WNL.0b013e3182020349. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Takashima Y, Mori T, Hashimoto M, et al. Clinical correlating factors and cognitive function in community-dwelling healthy subjects with cerebral microbleeds. J Stroke Cerebrovasc Dis. 2011 Mar-Apr;20(2):105–110. doi: 10.1016/j.jstrokecerebrovasdis.2009.11.007. [DOI] [PubMed] [Google Scholar]
- 11.Yakushiji Y, Noguchi T, Hara M, et al. Distributional impact of brain microbleeds on global cognitive function in adults without neurological disorder. Stroke. 2012 Jul;43(7):1800–1805. doi: 10.1161/STROKEAHA.111.647065. [DOI] [PubMed] [Google Scholar]
- 12.van Norden AG, van den Berg HA, de Laat KF, Gons RA, van Dijk EJ, de Leeuw FE. Frontal and temporal microbleeds are related to cognitive function: the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) Study. Stroke. 2011 Dec;42(12):3382–3386. doi: 10.1161/STROKEAHA.111.629634. [DOI] [PubMed] [Google Scholar]
- 13.van Es AC, van der Grond J, de Craen AJ, et al. Cerebral microbleeds and cognitive functioning in the PROSPER study. Neurology. 2011 Oct 11;77(15):1446–1452. doi: 10.1212/WNL.0b013e318232ab1d. [DOI] [PubMed] [Google Scholar]
- 14.Werring DJ, Frazer DW, Coward LJ, et al. Cognitive dysfunction in patients with cerebral microbleeds on T2*-weighted gradient-echo MRI. Brain. 2004 Oct;127(Pt 10):2265–2275. doi: 10.1093/brain/awh253. [DOI] [PubMed] [Google Scholar]
- 15.Gregoire SM, Scheffler G, Jager HR, et al. Strictly lobar microbleeds are associated with executive impairment in patients with ischemic stroke or transient ischemic attack. Stroke. 2013 May;44(5):1267–1272. doi: 10.1161/STROKEAHA.111.000245. [DOI] [PubMed] [Google Scholar]
- 16.Hofman A, Darwish Murad S, van Duijn CM, et al. The Rotterdam Study: 2014 objectives and design update. Eur J Epidemiol. 2013 Nov;28(11):889–926. doi: 10.1007/s10654-013-9866-z. [DOI] [PubMed] [Google Scholar]
- 17.Ikram MA, van der Lugt A, Niessen WJ, et al. The Rotterdam Scan Study: design and update up to 2012. Eur J Epidemiol. 2011 Oct;26(10):811–824. doi: 10.1007/s10654-011-9624-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Loehrer E, Ikram MA, Akoudad S, et al. Apolipoprotein E genotype influences spatial distribution of cerebral microbleeds. Neurobiology of aging. 2014 Apr;35(4):899–905. doi: 10.1016/j.neurobiolaging.2013.09.012. [DOI] [PubMed] [Google Scholar]
- 19.de Boer R, Vrooman HA, van der Lijn F, et al. White matter lesion extension to automatic brain tissue segmentation on MRI. Neuroimage. 2009 May 1;45(4):1151–1161. doi: 10.1016/j.neuroimage.2009.01.011. [DOI] [PubMed] [Google Scholar]
- 20.Hoogendam YY, Hofman A, van der Geest JN, van der Lugt A, Ikram MA. Patterns of cognitive function in aging: the Rotterdam Study. Eur J Epidemiol. 2014 Feb;29(2):133–140. doi: 10.1007/s10654-014-9885-4. [DOI] [PubMed] [Google Scholar]
- 21.McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology. 1984 Jul;34(7):939–944. doi: 10.1212/wnl.34.7.939. [DOI] [PubMed] [Google Scholar]
- 22.Association AP. Diagnostic and Statistical Manual of Mental Disorders. 3. Washington, DC: American Psychiatric Association; 1987. rev ed. [Google Scholar]
- 23.Liem MK, Lesnik Oberstein SA, Haan J, et al. MRI correlates of cognitive decline in CADASIL: a 7-year follow-up study. Neurology. 2009 Jan 13;72(2):143–148. doi: 10.1212/01.wnl.0000339038.65508.96. [DOI] [PubMed] [Google Scholar]
- 24.Seo SW, Hwa Lee B, Kim EJ, et al. Clinical significance of microbleeds in subcortical vascular dementia. Stroke. 2007 Jun;38(6):1949–1951. doi: 10.1161/STROKEAHA.106.477315. [DOI] [PubMed] [Google Scholar]
- 25.Goos JD, Kester MI, Barkhof F, et al. Patients with Alzheimer disease with multiple microbleeds: relation with cerebrospinal fluid biomarkers and cognition. Stroke. 2009 Nov;40(11):3455–3460. doi: 10.1161/STROKEAHA.109.558197. [DOI] [PubMed] [Google Scholar]
- 26.Goos JD, Henneman WJ, Sluimer JD, et al. Incidence of cerebral microbleeds: a longitudinal study in a memory clinic population. Neurology. 2010 Jun 15;74(24):1954–1960. doi: 10.1212/WNL.0b013e3181e396ea. [DOI] [PubMed] [Google Scholar]
- 27.Pettersen JA, Sathiyamoorthy G, Gao FQ, et al. Microbleed topography, leukoaraiosis, and cognition in probable Alzheimer disease from the Sunnybrook dementia study. Arch Neurol. 2008 Jun;65(6):790–795. doi: 10.1001/archneur.65.6.790. [DOI] [PubMed] [Google Scholar]
- 28.Hanyu H, Tanaka Y, Shimizu S, Takasaki M, Abe K. Cerebral microbleeds in Alzheimer’s disease. J Neurol. 2003 Dec;250(12):1496–1497. doi: 10.1007/s00415-003-0245-7. [DOI] [PubMed] [Google Scholar]
- 29.Cordonnier C, van der Flier WM, Sluimer JD, Leys D, Barkhof F, Scheltens P. Prevalence and severity of microbleeds in a memory clinic setting. Neurology. 2006 May 9;66(9):1356–1360. doi: 10.1212/01.wnl.0000210535.20297.ae. [DOI] [PubMed] [Google Scholar]
- 30.Werring DJ, Gregoire SM, Cipolotti L. Cerebral microbleeds and vascular cognitive impairment. J Neurol Sci. 2010 Dec 15;299(1–2):131–135. doi: 10.1016/j.jns.2010.08.034. [DOI] [PubMed] [Google Scholar]
- 31.Tanaka A, Ueno Y, Nakayama Y, Takano K, Takebayashi S. Small chronic hemorrhages and ischemic lesions in association with spontaneous intracerebral hematomas. Stroke. 1999 Aug;30(8):1637–1642. doi: 10.1161/01.str.30.8.1637. [DOI] [PubMed] [Google Scholar]
- 32.Smith EE, Gurol ME, Eng JA, et al. White matter lesions, cognition, and recurrent hemorrhage in lobar intracerebral hemorrhage. Neurology. 2004 Nov 9;63(9):1606–1612. doi: 10.1212/01.wnl.0000142966.22886.20. [DOI] [PubMed] [Google Scholar]
- 33.Greenberg SM. Cerebral amyloid angiopathy and vessel dysfunction. Cerebrovasc Dis. 2002;13( Suppl 2):42–47. doi: 10.1159/000049149. [DOI] [PubMed] [Google Scholar]
- 34.Kwa VI, Franke CL, Verbeeten B, Jr, Stam J. Silent intracerebral microhemorrhages in patients with ischemic stroke. Amsterdam Vascular Medicine Group. Ann Neurol. 1998 Sep;44(3):372–377. doi: 10.1002/ana.410440313. [DOI] [PubMed] [Google Scholar]
- 35.Baumgartner RW, Sidler C, Mosso M, Georgiadis D. Ischemic lacunar stroke in patients with and without potential mechanism other than small-artery disease. Stroke. 2003 Mar;34(3):653–659. doi: 10.1161/01.STR.0000058486.68044.3B. [DOI] [PubMed] [Google Scholar]
- 36.Janaway BM, Simpson JE, Hoggard N, et al. Brain haemosiderin in older people: pathological evidence for an ischaemic origin of magnetic resonance imaging (MRI) microbleeds. Neuropathol Appl Neurobiol. 2014 Apr;40(3):258–269. doi: 10.1111/nan.12062. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Mesker DJ, Poels MM, Ikram MA, et al. Lobar distribution of cerebral microbleeds: the Rotterdam Scan Study. Arch Neurol. 2011 May;68(5):656–659. doi: 10.1001/archneurol.2011.93. [DOI] [PubMed] [Google Scholar]
- 38.Cordonnier C, van der Flier WM. Brain microbleeds and Alzheimer’s disease: innocent observation or key player? Brain. 2011 Feb;134(Pt 2):335–344. doi: 10.1093/brain/awq321. [DOI] [PubMed] [Google Scholar]
- 39.Drachman DA. The amyloid hypothesis, time to move on: Amyloid is the downstream result, not cause, of Alzheimer’s disease. Alzheimers Dement. 2014 May;10(3):372–380. doi: 10.1016/j.jalz.2013.11.003. [DOI] [PubMed] [Google Scholar]
- 40.Marchesi VT. Alzheimer’s dementia begins as a disease of small blood vessels, damaged by oxidative-induced inflammation and dysregulated amyloid metabolism: implications for early detection and therapy. FASEB J. 2011 Jan;25(1):5–13. doi: 10.1096/fj.11-0102ufm. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.