Blood Viscosity in Subcortical Vascular Mild Cognitive Impairment with versus without Cerebral Amyloid Burden Hyun J. Noh, MD,* Sang W. Seo, MD, PhD,* Yong Jeong, MD, PhD,† Jeong E. Park, MD, PhD,‡ Geon H. Kim, MD,x Young Noh, MD,jj Hanna Cho, MD,* Hee J. Kim, MD,* Cindy W. Yoon, MD,x Byong S. Ye, MD,* David J. Werring, PhD, FRCP,{ and Duk L. Na, MD*

Background: Subcortical vascular dementia (SVaD) is a common form of dementia, attributed to ischemic small-vessel disease. Blood viscosity (BV) may contribute to the pathophysiology of SVaD. However, SVaD patients with coexisting amyloid deposition may not show differences in BV because their small-vessel disease may result from amyloid angiopathy independently of BV. We, therefore, hypothesized that BV might show different changes compared with control subjects in subcortical vascular mild cognitive impairment (svMCI) that refers to the prodromal stage of SVaD according to cerebral amyloid burden detected by the [11C] Pittsburgh compound B (PiB) PET (positron emission tomography), and apolipoprotein 4 (ApoE4) genotype (a known risk factor for vascular and parenchymal amyloid). Methods: Our subjects consisted of 33 healthy normal controls (NC), 28 patients with PiB(2) svMCI, and 12 with PiB(1) svMCI. They underwent scanning capillary tube viscometer measuring BV during systolic and diastolic phases. Results: Compared with the NC group, the PiB(2) svMCI group showed increased diastolic blood viscosity (DBV) but no difference in systolic blood viscosity (SBV). By contrast, there was no significant difference in SBV and DBV between the NC and PiB(1) svMCI groups. Within the PiB(1) svMCI group, ApoE4(2) subgroup showed increased DBV compared with the ApoE4(1) subgroup. Conclusions: Increased DBV is an important contributor to the development of ‘‘pure’’ svMCI (ie, without cerebral amyloid deposition). The relationship between BV and PiB(1) svMCI differed according to ApoE genotype, suggesting that the pathogenesis of PiB(1) svMCI might also be heterogeneous. Key Words: Hemodynamic—amyloid—artherosclerosis—vascular dementia—MRI. Ó 2014 by National Stroke Association

From the *Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea; †Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea; ‡Department of Cardiology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea; xDepartment of Neurology, Inha University School of Medicine, Incheon, Korea; jjDepartment of Neurology, Gachon University Gil Medical Center, Incheon, Korea; and {Department of Brain Repair and Rehabilitation, University College of London Institute of Neurology, Queen Square, London, UK.

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Received June 28, 2013; revision received August 6, 2013; accepted August 9, 2013. Address correspondence to Sang W. Seo, MD, PhD, Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 50 Ilwon-dong, Kangnam-ku, Seoul 135-710, Republic of Korea. E-mail: [email protected]. 1052-3057/$ - see front matter Ó 2014 by National Stroke Association http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2013.08.004

Journal of Stroke and Cerebrovascular Diseases, Vol. 23, No. 5 (May-June), 2014: pp 958-966

BV IN sVMCI WITH VERSUS WITHOUT CEREBRAL AMYLOID BURDEN

Introduction Blood viscosity (BV) is the intrinsic resistance of blood to flow in vessels. It has been demonstrated that increased BV directly increases shear stress and inflammatory injury to blood vessels, ultimately affecting tissue perfusion.1 As a result, BV plays an important role in the pathogenesis of atherosclerosis,2,3 especially in cardiovascular diseases.4-6 BV varies with shear rate (defined as the ratio of velocity to lumen diameter) because blood is a non-Newtonian fluid.7 Recent studies suggested that BV at low shear rates of 5/s or less (diastolic blood viscosity [DBV]) is more important than BV at high shear rates of 300/s or more (systolic blood viscosity [SBV]) as a cardiovascular risk factor.8-11 Subcortical vascular dementia (SVaD) is one of the most common forms of vascular dementias, especially in Asian populations.12 Vascular risk factors including hypertension and diabetes are associated with arteriolosclerosis in small vessels, which in turn leads to small-vessel disease markers including white matter hyperintensities (WMH) and lacunes on magnetic resonance imaging (MRI). Recent studies showed that the flow of blood in small vessels is influenced by BV and systolic blood pressure8,13-15 and that BV might be an important new factor in the pathophysiology of SVaD.13,14 To our knowledge, there have been no studies examining BV in subcortical vascular mild cognitive impairment (svMCI), a transitional stage between normal aging and SVaD. Moreover, the previous studies did not evaluate BV at different shear rates. Because BV in small arteries increases more at slow blood velocities than high velocities,15 DBV (rather than SBV) might be selectively raised in svMCI patients. Some patients clinically diagnosed with SVaD have evidence of coexisting Alzheimer disease (AD) pathology.16-18 Pittsburgh compound B (PiB) is an amyloid PET tracer designed to bind to the fibrillar form of ß-amyloid.19-21 We previously showed that more than 30% of svMCI patients showed significant amyloid burdens quantified by PiB PET.22 Because PiB(2) svMCI may result solely from ischemic small-vessel disease (arteriolosclerosis), we hypothesized that these patients would have increased DBV compared with normal controls (NC). On the other hand, patients with PiB(1) svMCI might have combined arteriolosclerosis and amyloid pathology, so we hypothesized that there would be less or no differences in BV between NC and PiB(1) svMCI. Because apolipoprotein 4 (ApoE4) carriers are susceptible to the development of AD, we hypothesized that BV in PiB(1) svMCI would be different according to ApoE status.

Material and Methods Participants We prospectively recruited 67 patients with svMCI who underwent PiB PET at Samsung Medical Center from Oc-

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tober 2009 to May 2011. Patients with svMCI were diagnosed using the Petersen criteria23 with the following modifications: (1) a subjective cognitive complaint by the patient or his/her caregiver, (2) normal activity of daily living (ADL) score determined clinically and by the instrumental ADL scale with the cutoff point of 7,24 (3) an objective cognitive decline below the 16th percentile on the Seoul Neuropsychological Screening Battery (SNSB),25,26 (4) no dementia, (5) a subcortical vascular feature defined as a focal neurologic symptom/sign that included corticobulbar signs, pyramidal signs, or parkinsonism,27 and (6) significant small-vessel ischemia on MRI. The presence of significant ischemic changes associated with small-vessel disease was defined as WMH on T2-weighted or FLAIR (fluid-attenuated inversion recovery) images that satisfied the following criteria: (1) WMH of 10 mm or more in the periventricular white matter (caps or rim) and (2) WMH of 25 mm or more (maximum diameter) in the deep white matter, consistent with an extensive white matter lesion or diffusely confluent lesion. When defining the deep white matter, WMH located in the axial slice just above the tops of the lateral ventricles was considered to be a periventricular white matter lesion, whereas WMH in the second or higher axial slices above the tops of the lateral ventricles was considered to be a deep white matter lesion. These imaging criteria indicated that these patients had ischemia sufficient to meet at least grade 3 of the Fazekas ischemia criteria.28 Patients were evaluated by clinical interview and neurologic and neuropsychological examinations as previously described.29 To exclude secondary causes of cognitive deficits, all patients underwent laboratory tests, including complete blood count, blood chemistry, vitamin B12/folate, syphilis serology, and thyroid function tests. Brain MRI scanning confirmed the absence of structural lesions, including territorial cerebral infarction, brain tumor, hippocampal sclerosis, and vascular malformation. We recruited 33 subjects with normal cognition. The normal healthy control group consisted of individuals who had no cardiovascular risk factors such as hypertension, diabetes mellitus, hyperlipidemia, and ischemic heart disease and who exhibited normal performances on neuropsychological tests. We obtained written consents from each patient, and the Institutional Review Board of the Samsung Medical Center approved the study protocol.

Neuropsychological Tests All patients underwent neuropsychological testing, using the SNSB.25 This battery contains assessments of attention, language abilities, praxis, 4 elements of Gerstmann syndrome, visuoconstructive functioning, verbal and visual memory, and frontal/executive functioning. Among these subtests, the quantitatively scorable tests included the following: digit span (both forward and backward), the Korean version of the Boston Naming Test,30 the

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Rey–Osterrieth Complex Figure Test (copying, immediate and 20-minute delayed recall, and recognition), Seoul Verbal Learning Test (3 learning-free recall trials of 12 words, a 20-minute delayed recall trial for these 12 words, and a recognition test), phonemic and semantic Controlled Oral Word Association Test, and a Stroop Test (word and color reading of 112 items during a 2-minute period).

[11C] PiB PET All svMCI patients completed a [11C] PiB PET scan at Samsung Medical Center using a Discovery STe PET/ CT scanner (GE Medical Systems, Milwaukee, WI) using a standardized protocol. The detailed radiochemistry profiles and scanning protocol were described in a previous study.31

Data Analysis PiB PET images were coregistered to individual MRIs, which were normalized to a T1-weighted MRI template. Using these parameters, MRI coregistered PiB PET images were normalized to the MRI template. The quantitative regional values of PiB retention on the spatially normalized PIB images were obtained by an automated volume-of-interest (VOI) analysis using the automated anatomical labeling atlas. Data processing was performed using the SPM version 2 under Matlab 6.5 (Mathworks, Natick, MA). To measure PiB retention, we used the cerebral cortical region to cerebellum uptake ratio that is identical to the standardized uptake value ratios (SUVRs). The cerebellum was used as a reference region as it did not show group differences. We selected 28 cortical VOIs from left and right hemispheres using the automated anatomical labeling atlas. The cerebral cortical VOIs that were chosen for this study consisted of bilateral frontal (superior and middle frontal gyri, medial part of superior frontal gyrus, opercular part of inferior frontal gyrus, triangular part of inferior frontal gyrus, supplementary motor area, orbital part of superior, middle, and inferior orbital frontal gyri, rectus, and olfactory cortex), posterior cingulate gyri, parietal (superior and inferior parietal, supramarginal and angular gyri, and precuneus), lateral temporal (superior, middle, and inferior temporal gyri and heschl gyri), and occipital (superior, middle, and inferior occipital gyri, cuneus, calcarine fissure, and lingual and fusiform gyri). Regional cerebral cortical SUVRs were calculated by dividing each cortical VOI’s SUV by mean SUV of cerebellar cortex (cerebellum crus1 and crus2). Global PiB uptake ratio was calculated from the volume-weighted average SUVR of bilateral 28 cerebral cortical VOIs. We defined PiB uptake ratio as a continuous variable. Patients were considered PiB positive if their global PiB uptake ratio was more than 2 standard deviations (PiB retention ratio . 1.5) from the mean of the NC.

MRI Techniques T2, T1, FLAIR, and T2 Fast Field Echo MR images were acquired from all subjects at Samsung Medical Center using the same 3.0 T MRI scanner (Philips 3.0 T Achieva). In all patients, these images were obtained in 1 session, and all MR images were obtained in the same orientation and slice positions. FLAIR MR images were acquired in the axial plane with the following parameters: axial slice thickness of 2 mm; no gap; repetition time of 11,000.0 ms; echo time of 125.0 ms; flip angle of 90 ; and matrix size of 512 3 512 pixels.

Measurement of Regional WMH Volume Because the contrasting properties of FLAIR images allow automated segmentation and classification of WMH,32 FLAIR images were used to quantify WMH (Fig 1). The procedures for measuring regional WMH volume have been previously described.33 First, the WMH candidate region mask was generated using T1 images to remove the known sources of false-positive segmentation in the subarachnoid space and brain–cerebrospinal fluid interface. WMH segmentation was performed using FLAIR images only in the WMH candidate region, by applying the FMRIB Automatic Segmentation Tool of the FSL software (http://www. fmrib.ox.ac.uk/fsl/). Note that the FMRIB Automatic Segmentation Tool is based on a hidden Markov random field model and an associated expectation–maximization algorithm.

Assessment of Lacunes on MRI Two experienced neurologists (H.J.N. and S.W.S.), who were blinded to patients’ data, reviewed the number and location of the lacunes on MRI. The rate of agreement between the 2 lacunes was counted with the same method used in MB. The lacune was defined as a small lesion (#15 mm in diameter) with low signal on T1-weighted images, high signal on T2-weighted images, and perilesional halo on FLAIR images. Lacunes were counted in 4 cortical regions (frontal, parietal, temporal and occipital), subcortical regions (including the basal ganglia, thalamus, and white matter regions, which are not included cortical regions), and infratentorial regions. Cortical regions were defined as 10 mm or less from the brain surface.

BV Measurements Whole BV was measured with a scanning capillary tube viscometer (BVD [blood viscosity diameter] from Bio-Visco, Inc., S. Korea) at 37 C, which used a Ushaped tube with a capillary tube between 2 vertical tubes. The operating principle of the viscometer and the mathematical procedure to calculate BV using Casson model were given elsewhere.34 The blood samples

BV IN sVMCI WITH VERSUS WITHOUT CEREBRAL AMYLOID BURDEN

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Figure 1. The magnetic resonance imaging findings of (A) PiB(2) and (B) PiB(1) svMCI patients. Abbreviations: PiB, Pittsburgh compound B; svMCI, subcortical vascular mild cognitive impairment.

required for the viscosity tests were approximately 3 mL of whole blood with EDTA for anticoagulation. Whole blood viscosity (WBV) was measured over a wide range of shear rates from 1 to 1000/s. However, the present study reports WBV at 2 shear rates of 1 and 300/s. The BV measured at 1/s will be referred as DBV, whereas the WBV measured at 300/s will be referred as SBV in the study. Among 67 patients with svMCI, 45 patients (67.2%) showed PiB(2) and 22 patients showed PiB(1). Among 45 svMCI patients with PiB(2), BV was measured in 28 patients (63%), whereas among svMCI patients with PiB(1), BV was measured in 12 patients (54%). There were no significant differences in demographics, cerebrovascular risk factors, medication, ApoE4 allele, SVD MRI markers, and PiB retention between included and remaining patients (Table 1).

Statistical Analysis For descriptive statistics, chi-square test and analysis of variance were used to compare NC, PiB(2) svMCI, and PiB(1) svMCI in demographic and clinical characteristics.

To compare the SBV and DBV between NC and PiB(2) svMCI or between NC and PiB(1) svMCI, multiple linear regression analysis was performed. Age, gender, hematocrit (Hct), currently taking medication, and groups were included as independent variables. Because previous studies suggested that adenosine diphosphate (ADP) antagonists (clopidogrel and ticlopidine) and statin can have an influence on BV (ie, reducing BV),35-37 these mediations were included as independent variables. In addition, groups (NC, PiB(2) svMCI, and PiB(1) svMCI) were transformed as a dummy variable. To evaluate the relation of BV and SVD markers (ie, WMH, lacunes), we performed the multiple linear regression analysis adjusting age. In PiB(1) svMCI group, SBV and DBV were compared between ApoE4(1) subgroup and ApoE4(2) subgroup. Because there were no differences in age, gender, Hct, and currently taking medication including ADP antagonists (clopidogrel and ticlopidine) and statin between the 2 subgroups, we performed 2-tailed t test. The statistical significance was defined as P less than .05. We used a commercially available software (Statistical Package for Social Science, version 18.0; SPSS, Inc., Chicago, IL).

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Table 1. Comparison of demographic, clinical characteristics, SVD MRI markers, and PiB PET results between included and excluded subjects SvMCI with PiB(2), N 5 45 (67.2%) Parameter

Excluded subjects, n 5 17 (37%)

SvMCI with PiB(1), N 5 22 (32.8%)

Included subjects, n 5 28 (63%)

Demographics Age, y 72.9 6 6.6 74.8 6 6.8 Male, n (%) 7 (41.2) 12 (42.9) Cerebrovascular risk factors Hypertension, n (%) 12 (70.6) 25 (89.3) Diabetes, n (%) 4 (23.5) 6 (21.4) Hyperlipidemia, 2 (11.8) 7 (25.0) n (%) Heart disease, n (%) 5 (29.4) 6 (21.4) Medication — ADP antagonist, 3 (17.6) 9 (32.1) n (%) 2 (11.8) 7 (25.0) HMG CoA-reductase inhibitor, n (%) ApoE4(1), n (%) 2 (11.8) 18 (35.7) SVD MRI markers WMH, mm3 32,921.8 6 17939.5 34,446.2 6 18396.9 Lacunes, n 6 (2-20) 7 (1-13) PiB retention Retention ratio 1.24 6 .11 1.26 6 .09

P*

Excluded subjects, n 5 10 (46%)

Included subjects, n 5 12 (54%)

P*

.363 .912

75.0 6 4.6 6 (60.0)

79.3 6 7.0 4 (33.3)

.116 .221

.112 .447 .447

3 (30.0) 1 (10.0) 2 (20.0)

8 (66.7) 4 (33.3) 6 (50.0)

.087 .323 .204

.722

2 (20.0)

4 (33.3)

.484

.488

4 (40.0)

2 (16.7)

.348

.278

2 (20.0)

6 (50.0)

.204

.096

6 (60.0)

6 (50.0)

.691

.790 44,587.8 6 22164.9 32,057.5 6 13232.9 .139 .860 4 (0-7) 2 (1-5) .595 .523

2.09 6 .39

1.90 6 .27

.177

Abbreviations: ADP, adenosine diphosphate; ApoE4, apolipoprotein 4; BV, blood viscosity; HMG CoA, 3-hydroxyl-3methyl-glutaryl coenzyme; MRI, magnetic resonance imaging; PiB, Pittsburgh compound B; SVD, small-vessel disease; svMCI, subcortical vascular mild cognitive impairment; WMH, white matter hyperintensity. All values are expressed mean 6 SD or median (interquartile range). *P value between by 2-tailed t test or chi-square test.

Results Demographic and Clinical Characteristics of Patients There were differences in age and Hct among the 3 groups. The NC group was younger and had lower Hct than the 2 svMCI groups. However, there were no differences in age, gender, Hct, cerebrovascular risk factors, medication, and SVD MRI markers between PiB(2) and PiB(1) svMCI groups. Detailed demographics, clinical characteristics, MRI findings, and PiB results are shown in Table 2.

SBV and DBV in NC, PiB(2) svMCI, and PiB(1) svMCI Groups DBV was significantly higher in PiB(2) svMCI group (256.8 6 53.9 mP) than in NC group (217.3 6 31.7 mP), controlling for age, gender, Hct, medication for ADP antagonist, and statin (B [SE] 5 38.532 [16.57], P 5 .016). However, there was no significant difference of DBV between NC and PiB(1) svMCI groups (214.5 6 43.1 mP) (B [SE] 5 15.35 [21.037], P 5 .406). There was no significant difference of SBV among NC (37.0 6 3.2 mP),

PiB(2) svMCI group (39.4 6 5.1 mP), and PiB(1) svMCI group (36.0 6 4.1 mP, Fig 2.) Within PiB(1) svMCI group, the comparison of SBV and DBV between ApoE4(1) subgroup and ApoE4(2) subgroup revealed significantly higher DBV in ApoE4(2) subgroup than ApoE4(1) subgroup (239.6 6 41.8 mP versus 189.4 6 28.9 mP, P 5 .036). However, there was no difference of SBV between the 2 subgroups (Fig 3).

Relationship between BV and SVD Markers There was no significant relationship between BV and SVD markers (WMH volume and the number of lacunes), in PiB(2) and PiB(1) svMCI patients (Table 3).

Discussion In this study, we found that patients with PiB(2) svMCI had increased DBV compared with NC. On the contrary, there were no differences in BV between NC and PiB(1) svMCI. However, within the PiB(1) svMCI group, ApoE4(2) subgroup showed an increased DBV compared with the ApoE4(1) subgroup. Taken together, our findings suggest that DBV may be an

SvMCI with PiB(1) (N 5 12)

Demographics Age, yy Male, n (%) Hct, %y Cerebrovascular risk factors Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Heart disease, n (%) Medication ADP antagonist, n (%) HMG CoA-reductase inhibitor, n (%) SVD MRI markers WMH, mm3 Lacunes, n PiB retention PiB(1), n (%) Retention ratio

NC (N 5 33)

SvMCI with PiB(2) (N 5 28)

Total

ApoE4(2) (N 5 6)

ApoE4(1) (N 5 6)

P*

67.3 6 4.8z 7 (21.2) 37.5 6 3.0z

74.8 6 6.8 12 (42.9) 43.4 6 4.4

79.3 6 7.0 4 (33.3) 41.6 6 4.1

79.5 6 7.7 1 (16.7) 41.0 6 3.5

79.0 6 6.9 3 (50) 42.2 6 4.9

.908 .545 .656

0 (0) 0 (0) 0 (0) 0 (0)

25 (89.3) 6 (21.4) 7 (25.0) 6 (21.4)

8 (66.7) 4 (33.3) 6 (50.0) 4 (33.3)

4 (66.7) 2 (33.3) 3 (50.0) 2 (33.3)

4 (66.7) 2 (33.3) 3 (50.0) 2 (33.3)

1.000 1.000 1.000 1.000

0 (0) 0 (0)

9 (32.1) 7 (25.0)

2 (16.7) 6 (50.0)

2 (33.3) 3 (50.0)

0 (0) 3 (50.0)

.455 1.000

34,446.23 6 18,396.9 7 (1-13)

32,057.5 6 13232.9 2 (1-5)

29,645.8 6 15214.5 2 (1-10)

34,469.2 6 11823.7 2 (0-3)

.553 .466

28 (100) 1.9 6 .3

0 (0) 1.3 6 .1

6 (100) 1.9 6 .2

6 (100) 1.9 6 .3

1.00.679

— — — — —

BV IN sVMCI WITH VERSUS WITHOUT CEREBRAL AMYLOID BURDEN

Table 2. Demographics, clinical characteristics, MRI findings, and PiB results in subjects

Abbreviations: ADP, adenosine diphosphate; ApoE4, apolipoprotein 4; Hct, hematocrit; MRI, magnetic resonance imaging; HMG CoA, 3-hydroxyl-3methyl-glutaryl coenzyme; NC, normal controls; PiB, Pittsburgh compound B; svMCI, subcortical vascular mild cognitive impairment; SVD, small-vessel disease; WMH, white matter hyperintensities. All values are expressed mean 6 SD or median (interquartile range). *P value between svMCI with PiB(1) ApoE4(2) and svMCI with PiB(1) ApoE4(1) by 2-tailed t test or chi-square test. yOverall significance of analysis of variance across 3 different groups (NC, svMCI with PiB(2), and svMCI with PiB(1)). zSignificant difference as compared with other group.

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H.J. NOH ET AL. Figure 2. Comparison of SBV and DBV among NC, PiB(2), and PiB(1) svMCI groups. (A) There was no significant difference of SBV between NC, PiB(2) svMCI group, and PiB(1) svMCI group. (B) DBV was significantly higher in PiB(2) svMCI group than in NC group controlling for age, gender, Hct, medication for ADP antagonist, and statin. There was no significant difference of DBV between NC and PiB(1) svMCI groups. Note 10 mP 5 1 cP. Abbreviations: ADP, adenosine diphosphate; DBV, diastolic blood viscosity; Hct, hematocrit; NC, normal controls; PiB, Pittsburgh compound B; SBV, systolic blood viscosity; svMCI, subcortical vascular mild cognitive impairment. (Color version of figure is available online.)

important contributor to the development of ‘‘pure’’ svMCI but not in patients with cerebral amyloid deposition. Furthermore, the relationship between BV and PiB(1) svMCI differed according to the ApoE genotype, suggesting that the pathogenesis of PiB(1) svMCI might also be heterogenous. Our first major finding was that PiB(2) svMCI had increased DBV compared with NC. Traditionally, vascular risk factors, especially hypertension, are considered to contribute to arteriosclerosis, which leads to WMH or lacunes and SVaD.15 BV is a recently proposed risk factor for SVaD. Plasma proteins including fibrinogen, immunoglobulins, and lipoproteins are increased in SVaD, which may contribute to RBC aggregation38,39 and increased BV, which in turn may cause decreased cerebral blood flow and ischemic injury.7 Our finding suggests that increased BV might play an important role even in the development of the prodromal stage of SVaD. The explanation of why svMCI showed a difference in BV in the diastolic phase but not the systolic phase remains uncertain. In the diastolic phase, blood approaches stasis,7 allowing more chance for the intermolecular reactions among the plasma proteins such as fibrinogen, immunoglobulin, and lipoprotein. On the other hand, in the systolic phase, the increased velocity disperses the intermolecular reactions including the aggregation of erythrocytes. Indeed, it is suggested that the aggregation of

erythrocyte by other intermolecular reactions is one of the key components of DBV, whereas SBV is mainly influenced by erythrocyte deformability.35 Thus, our findings suggested that the intermolecular reaction of plasma proteins and erythrocyte aggregation might be one of the important pathophysiological mechanisms underlying ‘‘pure’’ svMCI. We found no relationship between BV and SVD markers such as WMH and lacunes. This finding implies that hyperviscosity might contribute to the development of svMCI through other routes rather than WMH or lacunes. In fact, previous studies suggested that microstructural changes or microinfarctions that were not able to be detected by conventional MRI might affect cognitive impairments in SVaD.40 Further prospective studies are needed to evaluate exactly how hyperviscosity may contribute to the development of svMCI. Our second major finding was that there were no differences in BV between NC and PiB(1) svMCI. This result suggests that the BV differentially affects the pathophysiology of small-vessel disease depending on the degree of cerebral amyloid deposition measured by PiB imaging. It may be explained that additional mechanism of smallvessel disease, not affected by BV, may exist in PiB(1) svMCI group. The processes underlying amyloid deposition in small- or medium-sized arteries leading to amyloid angiopathy may be independent of BV and Figure 3. Subgroup analyses of PiB(1) svMCI group. (A) Comparison of SBV between ApoE4(1) and ApoE4(2) subgroups. (B) Comparison of DBV between ApoE4(1) and ApoE4(2) subgroups. Note 10 mP 5 1 cP. Abbreviations: ADP, adenosine diphosphate; ApoE4, apolipoprotein 4; DBV, diastolic blood viscosity; Hct, hematocrit; NC, normal controls; PiB, Pittsburgh compound B; SBV, systolic blood viscosity; svMCI, subcortical vascular mild cognitive impairment. (Color version of figure is available online.)

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Table 3. Relationship between BV and SVD markers SvMCI with PiB(2), N 5 28 DBV

SvMCI with PiB(1), N 5 12

SBV

DBV

SBV

Parameters

B (SE)*

P

B (SE)

P

B (SE)

P

B (SE)

P

WMH volume, mm3 Total lacune

24.89 (69.79) 2.027 (.030)

.725 .380

907.59 (703.57) 2.154 (.320)

.210 .635

2118.74 (103.32) 2.040 (.069)

.288 .579

21139.91 (855.83) 2.433 (2.760)

.220 .469

Abbreviations: svMCI, subcortical vascular mild cognitive impairment; PiB, Pittsburgh compound B; DBV, diastolic blood viscosity; SBV, systolic blood viscosity; SVD, small-vessel disease; WMH, white matter hyperintensities. *Regression coefficient (SE).

arteriolosclerosis.41 Moreover, in our subgroup analysis of PiB(1) svMCI, the ApoE4(2) group had increased DBV compared with ApoE4(1) group. Since ApoE4 carriers are genetically susceptible to the development of CAA and AD and their MCI might be more closely related to CAA or AD than in the ApoE4(2) subgroup, the pathogenesis of PiB(1) svMCI might be different according to the ApoE4 genotype. Thus, the pathogenesis of PiB(1) svMCI might be different according to the ApoE4 genotype. There are some limitations to the present study. First, we did not recruit the whole svMCI cohorts although there were no differences in the demographics and clinical manifestations between included and the excluded subjects. Second, most svMCI patients were taking medications that could alter BV such as antiplatelet ADP antagonists36 and lipid-lowering agents.42 Although we corrected these factors statistically, there is still a possibility of underestimating BV in svMCI patients. Nevertheless our study is the first to demonstrate that DBV is associated with ‘‘pure’’ svMCI but not with svMCI where amyloid deposition is also present. The relationship between BV and PiB(1) svMCI differed according to the ApoE genotype, suggesting that the pathogenesis of PiB(1) svMCI might also be heterogenous. Finally, we did not measure BV in PiB(2) SVaD patients, which might be related to our finding that there were no relationship between BV and the severity of small-vessel disease. Acknowledgment: This study was supported by the Korean Healthcare Technology R&D Project Ministry for Health & Welfare Affairs, Republic of Korea (HI10C2020 & HIC120713), by the KOSEF NRL program grant (MEST; 2011-0028333), by Samsung Medical Center (CRL108011&CRS110-14-1), and by the Converging Research Center Program through the Ministry of Science, ICT and Future Planning, Korea (2013K000338). The authors acknowledge useful discussions on the operating principle of scanning capillary tube viscometer with Prof. Y.I.Cho at Drexel University, Philadelphia, PA.

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