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CD62-mediated activation of platelets in cerebral white matter lesions in patients with cognitive decline
Archives of Gerontology and Geriatrics 62 (2016) 118–124
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CD62-mediated activation of platelets in cerebral white matter lesions in patients with cognitive decline Nagato Kuriyamaa,b,* , Toshiki Mizunob , Hiromi Yasuikeb , Hiroyuki Matsunoc , Eri Kawashitac , Aiko Tamurab , Etsuko Ozakia , Daisuke Matsuia , Isao Watanabea , Teruhide Koyamaa , Fumitaro Miyatania , Masaki Kondob , Takahiko Tokudab , Youichi Ohshimab , Manabu Muranishib , Kentaro Akazawad, Akihiro Takadae , Kazuo Takedae , Sanae Matsumotoe , Shigeto Mizunof , Kei Yamadad, Masanori Nakagawab , Yoshiyuki Watanabea a
Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Japan Department of Neurology, Kyoto Prefectural University of Medicine, Japan Department of Clinical Pathological Biochemistry, Doshisha Women’s Collage, Japan d Department of Radiology, Kyoto Prefectural University of Medicine, Japan e Kyoto Industrial Health Association, Japan f Department of Medical Pharmaceutics, Kobe Pharmaceutical University, Japan b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 18 May 2015 Received in revised form 2 September 2015 Accepted 4 September 2015 Available online 12 September 2015
Background: Vascular dementia is related to intracranial arteriosclerosis associated with deep white matter lesions (DWMLs). DWMLs have been linked to thrombogenesis due to sustained platelet activation; therefore, an accurate hematological marker is needed. This study was done to evaluate the usefulness of a new method to examine the function of activated platelets in order to assess DWMLs associated with cognitive decline. Methods: A total of 143 individuals (70.4 6.1 years old) who underwent hospital-based health screening using head MRI were evaluated. DWLs were evaluated on T2-weighted and FLAIR images by semiquantitatively grading them from Grade 0 (none) to Grade 3 (severe) using the Fazekas classification. Cognitive function was evaluated using the MMSE and the word fluency test. Platelet activation was assessed using fluorescence-labeled anti-human platelet monoclonal antibodies and semi-quantitatively determining PAC-1- and CD62P-positive rates by flow cytometry. Results: Significant increases in hypertension and CD62P levels were observed with increasing DWML grade (2.6% in Group 0, 3.1% in Group 1, 4.1% in Group 2, and 5.0% in Group 3). CD62P levels were defined as elevated when they were above the mean + 2SD of the Grade 0 group, and the odds ratio of the Grade 2 + 3 group was 3.03. A significant negative correlation was observed between CD62P levels and word fluency tests or the MMSE score. Conclusion: Elevations in CD62P levels, which reflect platelet function activation, were associated with white matter lesions accompanied by a decline in cognitive function. CD62P levels may be useful as a sensitive clinical marker for the early detection of DWMLs with cognitive decline. ã 2015 Elsevier Ireland Ltd. All rights reserved.
Keywords: Deep white matter lesion (DWML) Cognitive decline Platelet activation CD62P
1. Introduction The incidence of vascular dementia has increased recently. An epidemiological study reported that this disease affects 2.5%
* Corresponding author at: Department of Epidemiology for Community Health and Medicine, and Department of Neurology, Kyoto Prefectural University of Medicine, Kyoto 602-8566, Japan. Fax: +81 752515799. E-mail address: [email protected] (N. Kuriyama). http://dx.doi.org/10.1016/j.archger.2015.09.001 0167-4943/ ã 2015 Elsevier Ireland Ltd. All rights reserved.
of people aged over 65 years (Sekita et al., 2010). As an etiological factor, the progression of deep white matter lesions (DWMLs) is known to be closely related to vascular dementia (Gouw et al., 2008; Schmidt et al., 2007). To date, a basic therapy for dementia has not yet been established. With the rapid aging of society, the prevention of DWMLs and their progression may decrease the number of elderly people with cognitive decline, thereby raising an important therapeutic issue (Fazekas et al., 1993; Fernando et al., 2004). However, no
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clinical parameter has yet been identified that can accurately evaluate DWMLs associated with cognitive decline. Cerebral white matter lesions reflect arteriolosclerosis and a chronic reduction in cerebral circulation, and platelet activation may be primarily involved (Fujita & Kawaguchi, 2002; Iwamoto et al., 1995). Chronic hypocirculation involving platelets and hyperaggregability play important roles in the pathogenesis of cerebral infarction, as reported previously (Kuriyama et al., 2010). In clinical practice, antiplatelet drugs that inhibit the functions of platelets have been used to prevent the deterioration of thrombotic arteriosclerotic lesions in the brain, because platelets play the most important role in the pathogenesis of thrombus formation in arteries (Adams et al., 2008; Committee, ESOEE, 2008). However, few studies have investigated whether DWMLs with chronic circulatory disorders and cognitive decline are directly associated with platelet function. Platelets may be activated and aggregate with age, thereby contributing to the progression of arteriosclerosis (Couch & Hassanein, 1976). The importance of a method to accurately evaluate the grade of platelet activation by assessing the level of an antigen that appears on the membrane surface with platelet activation has recently been suggested. Araki et al. (participating in our collaborative study) recently reported that activated platelets that expressed PAC-1 and CD62 were clinically sensitive and important as a marker reflecting the mechanism underlying thrombus formation in arteries (Araki et al., 2009; Shattil et al., 1987). Therefore, the aim of the present study was to clarify whether DWMLs were related to platelet activation as a new evaluation method in a general elderly population using an MRI-based design. Since platelet activation may be an important predictor of the incidence of DWML-related cognitive decline, the expressions of PAC-1 and CD62 on circulating platelets were investigated in patients with various stages of DWMLs, and their relationships with cognitive decline were evaluated. Whether platelet activation was a risk factor for intracranial DWMLs with cognitive decline, as well as their progression, was also examined in a general elderly population.
MMSE Score
2. Materials and methods 2.1. Study subjects A total of 143 participants (86 males, 57 females; 70.4 6.1 years old) who had voluntarily participated in a hospital-based health check-up and underwent brain MRI examinations in 2013 in Kyoto Prefecture were recruited. Subjects with a past or recent history of brain infarction, cardiovascular disease including myocardial infarction, renal failure, or specific neurological disorders such as multiple sclerosis, inflammatory diseases such as systemic lupus erythematosus, or apparent depression and dementia, and those prescribed antiplatelet drugs were excluded from this study. All participants underwent MR evaluations in addition to routine health check-up examinations following a random mailing recruitment approach. One subject dropped out due to the implantation of a pacemaker. The study protocol was approved by the Ethics Committee of our institution, and written, informed consent was obtained from all participating subjects. 2.2. Evaluation of brain MRI Individual brain MRI scans were performed in all subjects using a 1.5-T scanner (Achieva 1.5T, Koninklijke Philips N.V., Eindhoven, The Netherlands), and the findings obtained were evaluated blindly by two board-certified neurologists (N.K., A.T.) and one board-certified radiologist (K.A.). The routine protocol of brain MRI included T1-weighted images (repetition time [TR], 611 ms; echo time [TE], 13 ms), T2-weighted images (TR, 4431 ms; TE, 100 ms), and fluid-attenuated inversion recovery (FLAIR) images (delay time [TI], 2200 ms; TR, 8000 ms; TE, 100 ms). Transverse imaging was performed using 5-mm-thick sections. These protocols were described in our previous MR-based clinical studies (Kuriyama et al., 2014, 2013; Ohshima et al., 2013). In the present study, T2-weighted and FLAIR images were individually assessed to evaluate DWLs, which were graded semiquantitatively from Grade 0 (none) to Grade 3 (severe) according to the Fazekas classification (Fazekas, Chawluk, Alavi, Hurtig, & Zimmerman, 1987). The severity of DWLs was assessed according to the presence of hyperintense lesions in the deep white matter: Grade 0, absent; Grade 1, punctate foci; Grade 2, confluent foci; and Grade 3, extensive confluent foci (Fig. 1). Grade 0–1 DWML was then defined as none/mild DWML, and grade 2–3 DWML was
World Fluency TA
Score
30
35 30 25 20
8
15
15
6
0
5 10 Percentage of platelets expressing CD62P
Score
14 10
20
World Fluency animal
16 12
25
4
10
2
5
0
119
0
5 10 Percentage of platelets expressing CD62P
0
0
5 10 Percentage of platelets expressing CD62P
Fig. 1. Relationships between platelet expression levels of CD62P and cognitive function scores. The relationship between the expression levels of the surface marker, CD62P, and higher cognitive function was investigated. A negative correlation is observed between CD62P values and MMSE/word fluency test scores (number of correct answers for generated words beginning with “Ta” and animal names) (r = 0.45, 0.51, and 0.48, respectively) (*: all p < 0.05). A significant decrease is observed in MMSE and word fluency scores with an increased percentage of CD62P-expressing platelets (*: p < 0.05).
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defined as marked DWML. Periventricular hyperintensity (PVH) on brain MRI evaluations was also defined according to the de Groot classification (de Groot et al., 2000).
time [s]) is generally assessed by measuring the time that a pulse wave takes to go forth and back between a given distance along a blood vessel and can provide an objective index of atherosclerosis (Lehmann et al., 1998).
2.3. Evaluation of covariates and cognitive function The relationships between various clinical vascular risk factors including% platelet activation were examined in the study group during their visit in 2013 in order to identify the main parameters significantly affecting DWMLs. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) (Folstein, Folstein, & McHugh, 1975). Scores on a 30-point scale were recorded by trained neurologists or a neuropsychologist. MMSE can be universally applied to assess orientation, attention, recall, and language ability, but it is considered insensitive as a global screening test for mild to moderate cognitive impairment. While the MMSE is assumed to assess general cortical cognitive function, a letter fluency test (Cerhan et al., 2002) and word fluency tasks (number of generated words) (Henry, Crawford, & Phillips, 2004; Pasquier, Lebert, Grymonprez, & Petit, 1995) were also performed as representative screening indicators of subcortical cognitive impairments. Subjects were asked to provide as many words beginning with “Ta” as they could recall for the letter fluency task and as many animal names as they could recall for the word fluency task. The scores obtained were the total numbers of correct answers for the generated words in each fluency test. These verbal fluency tasks were administered by trained neuropsychiatric therapists. The cognitive examinations performed on the same day before MR scanning in 2013 were the same as those described in our previous studies (Kuriyama et al., 2014, 2013; Ohshima et al., 2013). Routine peripheral blood and biochemistry examinations were performed as part of the health-screen check-up. Regarding the evaluation of covariates, the classical risk factors examined included: age, sex, HT (systolic blood pressure more than 140 mmHg, diastolic blood pressure more than 90 mmHg; or a history of HT plus antihypertensive medication), diabetes mellitus (DM) (fasting glucose more than 126 mg/dL or treatment with insulin or oral hypoglycemics); hyperlipidemia (HL) (total cholesterol more than 220 mg/dL, low density lipoprotein cholesterol (LDL) more than 140 mg/dL, or treatment with lipid-reducing drugs), and body mass index (BMI; kg/m2). These covariates were obtained during the measurements collected in 2013. In this analysis, a drinker was defined as an individual who had typically been drinking more than 20 g of alcoholic beverages daily for 1 year or longer (Yokoyama, Hiroshi, Ohgo, Hibi, & Saito, 2007). Smoking was also defined as a current smoker who smoked daily, or a former smoker who had quit smoking by the time of this study. These lifestyle factors or behaviors were confirmed using a selfcompleted questionnaire. Since Apoprotein E (APOE) e4 gene is the major known genetic risk factor for cognitive decline, the APOE e4 gene was genotyped, and the number of APOE e4 alleles carried by each subject was determined using commercially available assays (Funakoshi Co., Ltd., Tokyo, Japan). We identified the subjects with the presence of APOE e4 allele as more than one APOE e4 allele (1 APOE e4 allele). Brachial-ankle pulse wave velocity (PWV), a validated noninvasive measurement that represents arterial stiffness, was measured in subjects using a form-I automated PWV/ABI analyzer (Omron Co., Ltd., Kyoto, Japan) attached to the four limbs (Yamashina et al., 2002). The cuffs were wrapped around both upper arms and ankles, with patients resting in the supine position, following a 15-min rest. Pulse volume waveforms at the upper arm and ankle were recorded using a semiconductor pressure sensor. Data are expressed as means standard deviation. Brachial-ankle pulse wave velocity (BaPWV) (=distance [m]/transit
2.4. Whole-blood flow cytometry and quantification of CD62 and PAC1 expression levels Specifically, 2 ml of venous blood were collected in a bloodcollection tube containing acid sodium citrate using a 21-G needle, and they were left for 15 min at room temperature. To avoid spontaneous platelet activation, the first portion of 2 ml was discarded from the blood samples. Then 10 ml of the collected whole blood were transferred to 5 ml of a polystyrene round bottom test tube (BD FalconTM, Catalog Number 352052, Tokyo, Japan), 500 ml of BD Cell FixTM (BD Biosciences, Catalog Number 340181, Tokyo, Japan) were immediately added for fixation, and the mixture was then stored at 4 C until measurement. The resultant platelets were washed with HEPES buffer and resuspended to 4 108 cells/ml for FACS analysis. The FACS was performed within 6 h after blood collection. Platelets were examined for the surface expressions of activated antigens on the platelet membrane, and the percentages of CD62P and PAC-1 expressed by platelets were measured using flow cytometry, as described previously (Araki et al., 2009; Stellos et al., 2010). Specific monoclonal antibodies for CD62P and PAC-1 were used in the quantitative measurement of platelet surface expression. CD62P is an adhesion molecule that belongs to the P-selectin family. It is distributed on the platelet membrane surface with platelet activation, and, thus, is used as a representative marker of platelet activation (Hagberg & Lyberg, 2000). PAC-1 appears at the time of platelet activation-related structural changes in the glycoprotein IIb/IIIa complex on platelets. As PAC-1 expression increases rapidly, even in the presence of weak extra-platelet stimuli, it has been reported as a highly sensitive and specific marker of platelet activation. The platelet surface expression levels of CD62P and PAC-1 were further assessed by whole-blood flow cytometry using a fluorescein isothiocyanate-conjugated PAC-1 antibody and phycoerythrin-conjugated CD62p antibody. A saturating antibody concentration in 50 ml was added to 50 ml of whole blood. Negative control samples contained prepared IgG and IgM. Samples were incubated for 15 min at room temperature and then analyzed within 2 h by flow cytometry. Platelets were identified based on particle size and complexity using a peridimin-chlorophyll-conjugated CD61 antibody and PAC-1 antibody. Fluorescence data from 10,000 platelet events were collected. Expression levels were expressed as a percentage of positively identified platelets. All antibodies were purchased from BD Biosciences (San Jose, CA, USA). 2.5. Statistical analysis Data were analyzed using SPSS Inc., software version 19.0 (SPSS Inc., Chicago, IL, USA). Background factors including sex, age, BMI, and classical vascular risk factors were compared among DWL grade groups using one-way analysis of variance (ANOVA) or the x2 test. Spearman’s rank correlation test was used to assess the relationship between the percentage of activated platelets and cognitive function. The relationships between the parameters associated with the severity of DWMLs were examined using logistic regression analysis. The significance of between-group differences was evaluated using the OR (odds ratio) of the logistic regression analysis. Crude and adjusted (sex, age, HT, DM, HL, PVH, alcohol drinking, smoking, PVH (periventricular hyperintensity), PWV
N. Kuriyama et al. / Archives of Gerontology and Geriatrics 62 (2016) 118–124 Table 1 Clinical characteristics of all subjects.
Age Weight (kg) Height (cm) BMI (kg/m2) Systolic BP (mmHg) Diastolic BP (mmHg) Blood platelet count (104) Hypertension (%) Diabetes mellitus (%) Hyperlipidemia (%) Smoking (%) Alcohol intake (%) Anti-platelet drugs (%)
M SD M SD M SD M SD M SD M SD M SD
Total n = 143
Males n = 86
Females n = 57
70.4 6.1 57.9 10.2 160.2 9.4 22.4 2.7 129.1 15.0 74.5 10.0 21.2 6.1 53 (37.1%) 14 (9.8%) 43 (30.1%) 9 (6.3%) 60 (42.0%) 13 (9.1%)
70.6 5.8 63.2 7.9 165.9 6.1 23.0 2.1 131.0 14.4 77.0 9.1 22.0 7.2 38 (44.2%) 11 (12.8%) 23 (26.7%) 7 (8.1%) 48 (55.8%) 11 (12.8%)
70.0 6.4 49.6 7.4 151.5 6.0 21.7 3.4 125.9 16.7 70.6 10.4 20.8 5.8 15 (26.3%) 3 (5.3%) 20 (35.1%) 2 (3.5%) 12 (21.1 %) 2 (3.5%)
BMI: Body Mass Index; BP: blood pressure; M SD: mean standard deviation.
(pulse wave velocity >1800), the presence of APOE e4 allele, and the use of anti-platelet drugs) ORs with 95% confidence intervals (CIs) were calculated, with p < 0.05 being considered significant. 3. Results The clinical characteristics of the participants in this survey are shown in Table 1; the percentage of HT was higher in males (44.2%) than in females (26.3%), but blood pressure was well controlled in all subjects at the health check-up. No significant differences were observed in the blood platelet count or other platelet-related vascular risk factors between male and female subjects. Regarding the number of cases of each grade, as shown in Table 2, 55 subjects had Grade 0 (mean age 68.4 5.2 years), 55 had Grade 1 (mean age 70.2 5.6 years), 19 had Grade 2 (mean age 74.3 6.4 years), and 14 subjects had Grade 3 (mean age 74.2 7.1 years). Clinical background factors are shown in Table 2
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(upper row). The numbers of patients with hypertension and those with PVH increased significantly with the progression of white matter lesions, that is, with increased grade (p < 0.05). Concerning the other representative arteriosclerosis-associated factors, hypercholesterolemia and diabetes mellitus, no significant increase was observed with increased grade, which differed from the above results. The pulse wave velocity (PWV) was also measured due to the possibility of platelet activation at the peripheral blood vessel level; however, no significant differences were observed among the groups. Regarding the APOE e4 allele, there was no statistical trend for association between the presence of APOE e4 allele and grading of white matter lesions. Regarding the cognitive function tests, the results of grading based on brain MR findings are summarized in Table 2 (lower row). The MMSE and word fluency test scores decreased significantly with the progression of white matter lesions (grade) (p < 0.05). To investigate the relationship between risk factors and PAC-1/ CD62P values in the G0 to G3 groups, to which the subjects were assigned based on brain MR findings, CD62P and PAC-1 values were examined according to the grading of white matter lesions. As shown in Table 2 (lower row), CD62P values were 2.6%, 3.1%, 4.1%, and 5.0% in the G0, G1, G2, and G3 groups, respectively. Thus, this parameter increased significantly with the white matter lesion grade (p < 0.01). On the other hand, the PAC-1 value also increased gradually with the white matter lesion grade; however, no significant differences were observed among the groups, which differed from the results for the CD62P values. Therefore, CD62P was investigated alone in subsequent multivariate analyses. In these multivariate analyses, a mean CD62P value + 2 S.D. (6.1%) of the G0 group or higher was regarded as high. As shown in Table 3, the odds ratio for high CD62P values between 2 groups was calculated, that is, between a group with moderate and severe white matter lesions (the G2 + G3 group) and a group without and with slight white matter lesions (the G0 + G1 group). With respect to high CD62P values, the crude odds ratio in the G2 + G3 group was
Table 2 Clinical characteristics, %CD62 & PAC1-expressing platelets, and cognitive scores by group, and logistic regression analysis of variables in the DWL and DWLP groups.
General clinical characteristics Age (M SD) Hypertension (%) Diabetes mellitus (%) Hyperlipidemia (%) Smoking (%) Alcohol intake (%) HbA1c (%) (M SD) Smoking(%) PWV (m/s) (M SD) PVH (%) 1 ApoE e4 allele. No. (%) Cognitive function score MMSE (M SD) Word fluency animal (M SD) Word fluency TA (M SD)
G0 (n = 55)
G1 (n = 55)
G2 (n = 19)
G3 (n = 14)
p value
68.4 5.2
70.2 5.6
74.3 6.4
74.2 7.1
p = 0.012
16(29.1%) 6(10.9%) 14(25.5%) 4(7.3%) 24(43.6%) 5.7 0.5
22(40.0%) 4(7.3%) 17(30.9%) 3(5.5%) 22(40.0%) 5.8 0.9
7(36.8%) 2(10.5%) 7(36.8%) 1(5.3%) 8(42.1%) 5.9 0.8
8(57.1%) 2(14.3%) 5(35.7%) 1(7.1%) 6(42.9%) 5.6 0.3
p = 0.034* p = 0.895 p = 0.403 p = 0.894 p = 0.769 p = 0.662
3(5.5%) 1328.9 236.2
4(7.3%) 1317.7 216.9
1(5.3%) 1358.9 271.1
1(7.1%) 1331.9 313.1
p = 0.891 p = 0.542
11(20.0%) 6(10.9)
28(50.1%) 5(9.1)
17(89.5%) 2(10.5)
14(100%) 2(14.3)
p = 0.023* p = 0.240
28.9 1.7 17.2 4.8 9.2 3.8
28.1 1.9 16.4 4.4 7.4 2.8
26.7 2.8 15.3 3.4 7.2 2.3
26.4 2.0 14.7 5.1 6.9 3.0
p = 0.032* p = 0.045* p = 0.042*
3.1 1.3 2.9 1.6
4.1 1.5 3.4 1.8
5.0 1.3 3.6 1.4
**
1.1 0.6
1.5 1.3
0.8 0.5
p = 0.402
Quantification of CD62 & PAC1 expressions CD62P (%) (M SD) 2.6 1.0 PAC1 (%) 2.7 1.1 (M SD) 0.9 0.5 PAC1/CD62 (%) (M SD)
p < 0.01 p = 0.059
M SD: mean standard deviation; one-way analysis of variance (ANOVA) for measured values and the chi-square test for the categorical values were used for the analysis. * p < 0.05. ** p < 0.01.
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Table 3 Logistic regression analysis of variables in CD62 & PAC1-expressing platelets in the DWL and DWLP groups. G0 & G1 (n = 110) mild DWLM
G2 & G3 (n = 33) apparent DWML
G2 & G3 (n = 33) apparent DWML
CD62P > 6.1 (%)
3 (2.7)
13 (39.4) Model 1 OR (95% CI)
13 (39.4) Model 2 OR (95% CI)
CD62P > 6.1 (%)
Reference
6.07 (1.3–18.6)*
3.03 (1.8–9.4)*
OR: Odds ratio; CI: confidence interval; Model 1: adjusted by sex and age; Model 2: adjusted by sex, age, hypertension, diabetes mellitus, hyperlipidemia, alcohol drinking, smoking, PVH (periventricular hyperintensity), PWV (pulse wave velocity > 1800), the presence of APOE e4 allele, and anti-platelet drug treatment. * p < 0.05.
6.07 (95% confidence interval (CI): 1.3–18.6) in comparison with the G0 + G1 group. Multiple logistic regression analysis with adjustment for all possible confounding factors was used, because of the potential for bias with the voluntary sample selection. Adjustments were performed for multiple factors, including: sex, age for the DWML group, and other vascular risk factors such as hypertension, hyperlipidemia, diabetes mellitus, alcohol drinking, smoking, PVH (periventricular hyperintensity), high PWV (>1800 = mean + 2SD), the presence of APOE e4 allele, and the presence of antiplatelet drug therapy. The multivariate analysis for high CD62P values showed that the odds ratio in the G2 + G3 group was 3.03 (95% CI: 1.8–9.4) compared with the G0 + G1 group (p < 0.05), even after corrections for these relevant factors. As described above, a correlation was identified between CD62P values and DWML grades. Therefore, whether higher function test parameters were correlated with CD62P values was evaluated. A direct correlation was observed between MMSE scores and CD62P values (correlation coefficient: r = 0.45). Furthermore, there was a negative correlation between CD62P values and word fluency test scores (number of correct answers for generated words beginning with “Ta” and animal names) (r = 0.51, r = 0.48, respectively; both p < 0.05) (Fig. 1). 4. Discussion Sclerosis of arterioles penetrating the cerebral parenchyma accounts for the majority of cerebral white matter lesions, and many factors may be involved in its pathogenesis (Babikian & Ropper, 1987; Fazekas et al., 1993). As factors associated with white matter lesions other than hypertension and aging, previous studies identified diabetes mellitus and hyperlipidemia as vascular risk factors. Epidemiological surveys have also reported relationships between these factors (Breteler et al., 1994; de Leeuw et al., 2002). Our prospective cohort study showed that deep white matter lesions reduced cognitive function. Preventing the progression of white matter lesions represents an important therapeutic strategy for senile dementia (Kuriyama et al., 2013; Vermeer et al., 2003; Enzinger et al., 2007). Raz et al. found that platelet activation, which causes thrombus formation, played an important role in the deterioration of these cerebral white matter lesions, indicating the presence of platelet dysfunction, such as shortening of the platelet lifetime and platelet aggregation related to platelet activation as measured by the expression of glycoprotein IIb/IIIa or enhancement of plateletderived microvesicles (Raz et al., 2013). Furthermore, Fujita et al. (Fujita, Kawaguchi, Uehara, & Fukushima, 2005; Fujita & Kawaguchi, 2002) investigated the relationship between platelet activation and cerebral white matter lesions using a classical platelet aggregation test with adenosine diphosphate (ADP), and
they proposed that enhancement of platelet aggregation was an exacerbating factor. Concerning platelet function, measuring the level of the platelet-specific protein, b-thromboglobulin (bTG), and platelet aggregation tests have been recommended in addition to the above test (Mustard, Moore, Packham, & KinloughRathbone, 1977; Ohkawa et al., 2005). However, these platelet function-testing methods have not yet been standardized; their sensitivity is low, and there are various limitations for clinical use. On the other hand, a flow cytometry method was recently developed to evaluate the grade of platelet activation based on antigen expression on the membrane surface. This method requires a small volume of specimen, and operation methods are simple. Its reproducibility is good, facilitating high-sensitivity measurements. Thus, a new method to evaluate the grade of platelet activation has become available. However, no study has yet examined the brain MR findings of deep cerebral white matter lesions using this method. Araki et al. reported that PAC-1 and CD62 values were sensitive and important markers of platelet activation and reflected the mechanism underlying arterial thrombus formation. Based on this finding, we focused on cognitive decline in the presence of DWMLs and investigated the relationship between PAC-1/CD62 values and MR images/ cognitive function. Platelet aggregation is known to be enhanced in patients with intracerebral arteriosclerotic diseases. A previous study indicated that aging enhanced platelet aggregation, even in healthy adults (Couch & Hassanein, 1976). The present results also identified a relationship between age and the grade of deep cerebral white matter lesions and showed that CD62P values increased with age. As presented in Table 3, adjustments for multiple factors (including age) were performed for the DWML group (G2 + G3 group). The odds ratio for high CD62P values was 3.03 (95% CI: 1.8–9.4), which was significant. Furthermore, a negative correlation was observed between cognitive functions and CD62 values, as shown in Fig. 1. This result suggested that CD62P values were useful as an independent surrogate marker in the deep cerebral white matter lesion group with cognitive decline (DWML group). There have been some studies that found increased platelet expression of Pselectin associated with Alzheimer’s disease (Sevush et al., 1998; Stellos et al., 2010). It is possible that platelet activation also contribute to the pathogenesis of DWMLs associated with cognitive decline. Arteriosclerosis causes hypofunction or injury to vascular endothelial cells (Nabel, 1991). Platelet aggregation is regulated by endothelial cell functions. Therefore, when arteriosclerotic lesions involve an extensive area, the number of activated platelets increases due to endothelial cell hypofunction (Ruggeri, 2003). For example, systemic arteriosclerotic lesions have been detected in a large number of patients with Binswanger's disease, which is a typical disease of intracranial arteriosclerotic lesions (Babikian & Ropper, 1987; Iwamoto et al., 1995). These results indicate that arteriosclerotic lesions involving the whole body may enhance platelet aggregation in patients with severe white matter lesions. Therefore, PWV was measured as an index of systemic arteriosclerosis, and it was found to be slightly higher in the DWML group; however, no significant difference was noted by white matter lesion grade. Adjustments for multiple factors, including sex, age, PWV, and hypertension etc., were performed in the DWML group (G2 + G3 group), and the odds ratio for high CD62P levels was significant. These results suggest that continuous activation of platelets is an independent risk factor which is associated with DWMLs and cognitive decline. It is difficult to define what is meant by continuous platelet activation in this study; however, continuous platelet activation is reflected by platelet microaggregate formation, which is pathophysiologically active and is considered to markedly increase the risk of atherosclerosis and
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atherothrombosis caused by microcirculatory disorders (Ruggeri, 2002). However, one cannot completely rule out the possibility that platelet activation may be secondarily induced. A prospective, longitudinal follow-up survey needs to be performed after 3– 4 years in order to examine the course of DWMLs with high levels of CD62P and cognitive decline. Platelets in blood ejected from the heart pass through perfusion arteries in the brain over a specific period, and they are retained in the intracerebral microcirculation (Adams, 1998). Many platelets interact with vascular endothelial cells in intracerebral blood vessels, and they pass through them in an activation-prone state. Therefore, factors affecting the activation of platelets in circulating blood could include intracerebral microcirculatory disorders, as demonstrated by the present results. These intracerebral microcirculatory disorders may have occurred due to blood–brain barrier hypofunction, as in the DWML group. It has been speculated that the mechanism is mediated by inflammation, such as nitric oxide (NO) or interleukin signaling, as previously reported (Gremmel et al., 2015; Procter et al., 2015). Because Mezger et al. recently reported the correlation between vascular inflammation of the brain and platelets, the present observation could be explained by this kind of inflammatory reaction, and intracerebral microcirculatory disorders can contribute to inflammatory reactions via crosstalk both with immune cells and atherosclerotic endothelial cells in systemic arteriosclerotic arteries or arterioles, including the brain. Further basic evaluation may be needed to clarify this in the future (Mezger et al., 2015). Moreover, whether CD62P values can become a reliable surrogate index of prevention or a therapeutic approach towards DWML with cognitive decline is a next theme to be investigated, taking into consideration the effectiveness of anti-platelet drugs. On the other hand, a previous study suggested that DWMLs associated with cognitive decline are characterized by the release of physiological cognitive function-associated factors, such as beta-amyloid, in addition to a chronic decrease in blood flow (Debette & Markus, 2010). Recently, Marksteiner and Humpel (2013) conducted an in vitro experiment and found that platelets were carriers of beta-amyloid, which reduces cognitive function. Marksteiner and Humpel (2013) recently reported that activated platelets secreted beta-amyloid in Alzheimer patients, and these deposits increased with concomitant cognitive decline. They also reported that circulatory beta-amyloid released from activated platelets was incorporated into atherosclerotic vessels in in vitro systems. These findings implied that the secretion of betaamyloid-containing granule products from platelets may lead to the deposition of beta-amyloid in vascular dementia (Casoli et al., 2007). The present results showed that enhanced CD62-expression by platelets was associated with cognitive decline. Briefly, CD62mediated platelet activation may occur in cerebral white matter lesions with cognitive decline; beta-amyloid may be released by platelets activated in the brain, thus playing an important role in cognitive decline in patients with DWMLs. These changes may be impossible to evaluate using conventional platelet-measuring methods. Whether the level of beta-amyloid derived from platelets in patient serum can be measured in the future (Kitazume et al., 2012) is being reviewed. Moreover, because beta-amyloid is reported to increase from erythrocyte metabolism with aging, the interactions among these hemostatic factors are important as the next targets for our research (Kaminsky et al., 2013; Tikhonova et al., 2014). The present study has two major limitations. One is its relatively small sample size, resulting in insufficient statistical power to assess the hypothesis with a high degree of confidence. To evaluate the diagnostic value of CD62P, a large-scale cohort study is needed. The other limitation of this study is that it currently remains controversial whether platelet activation can be evaluated
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based on the results of a single cross-sectional study alone. Furthermore, the effect of platelet activation on cerebral white matter lesions has yet to be elucidated. To clarify these issues, further studies are needed to investigate whether platelet activation, as confirmed in this pilot study, leads to cognitive decline with the deterioration of cerebral white matter lesions after a few years. Platelet and cognitive functions need to be prospectively and continuously examined over 3 to 4 years, and then we can describe the substantive pattern of the CD62P levels and their effects on cerebral white matter lesions with cognitive decline. In addition, although there was no apparent correlation with APOE 4 allele and cerebral white matter lesions in the present study, we also plan to provide wide genetic profiles in the next health check-up survey, which will be crucial for the interpretation of our results. The pathological feature of CD62P for DWMLs has not yet been clearly defined; however, CD62P may be a clinical marker for the early detection of DWMLs with cognitive decline. We plan to include in our next investigation other useful markers of endothelium-dependent factors (Kosenko et al., 2012), such as NO-containing intermediate products of free radicals, to see if there is some relation with CD62P-related pathological elevations. 5. Conclusion Platelet activation was investigated with respect to the grade of white matter lesions, and its relationship with high CD62P values was confirmed. Furthermore, a direct relationship was observed between high CD62P values and word fluency scores. These results suggest that an increase in CD62P levels, which reflects the activation of platelet function, was associated with white matter lesions in patients with cognitive decline. Thus, conditions that enhance continuous platelet activation with blood-brain barrier hypofunction may be present in cerebral white matter lesions. CD62P values may be useful as a sensitive blood screening marker for cerebral white matter lesions in clinical practice. Conflict of interest The authors have no conflicts of interests. Acknowledgments This work was partially supported by a Grant-in-Aid for Scientific Research (B) (No. 19390178) and Grant-in-Aid for Scientific Research (C) (No. 24590809) from the Ministry of Education, Science, Sports, and Culture of Japan. References Adams, G. (1998). Exercise physiology laboratory manual. New York: W.C.B. McGraw Hill. Adams, R. J., Albers, G., Alberts, M. J., Benavente, O., Furie, K., & Goldstein, L. B., et al., (2008). Update to the AHA/ASA recommendations for the prevention of stroke in patients with stroke and transient ischemic attack. Stroke, 39, 1647–1652. Araki, S., Matsuno, H., Haneda, M., Koya, D., Kanno, Y., & Itho, J., et al., (2009). Correlation between albuminuria and spontaneous platelet microaggregate formation in type 2 diabetic patients. Diabetes Care, 32, 2062–2067. Babikian, V., & Ropper, A. H. (1987). Binswanger’s disease: a review. Stroke, 18, 2–12. Breteler, M. M., van Swieten, J. C., Bots, M. L., Grobbee, D. E., Claus, J. J., & van den Hout, J. H., et al., (1994). Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study. the rotterdam study Neurology, 44, 1246–1252. Casoli, T., Di, S., tefano, G., Giorgetti, B., Grossi, Y., Balietti, M., & Fattoretti, P., et al., (2007). Release of beta-amyloid from high-density platelets: Implications for alzheimer's disease pathology. Annals of the New York Academy of Sciences, 1096, 170–178. Cerhan, J. H., Ivnik, R. J., Smith, G. E., Tangalos, E. C., Petersen, R. C., & Boeve, B. F. (2002). Diagnostic utility of letter fluency, category fluency, and fluency difference scores in alzheimer’s disease. Clinical Neuropsychologist, 16, 35–42.
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CD62-mediated activation of platelets in cerebral white matter lesions in patients with cognitive decline Nagato Kuriyamaa,b,* , Toshiki Mizunob , Hiromi Yasuikeb , Hiroyuki Matsunoc , Eri Kawashitac , Aiko Tamurab , Etsuko Ozakia , Daisuke Matsuia , Isao Watanabea , Teruhide Koyamaa , Fumitaro Miyatania , Masaki Kondob , Takahiko Tokudab , Youichi Ohshimab , Manabu Muranishib , Kentaro Akazawad, Akihiro Takadae , Kazuo Takedae , Sanae Matsumotoe , Shigeto Mizunof , Kei Yamadad, Masanori Nakagawab , Yoshiyuki Watanabea a
Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Japan Department of Neurology, Kyoto Prefectural University of Medicine, Japan Department of Clinical Pathological Biochemistry, Doshisha Women’s Collage, Japan d Department of Radiology, Kyoto Prefectural University of Medicine, Japan e Kyoto Industrial Health Association, Japan f Department of Medical Pharmaceutics, Kobe Pharmaceutical University, Japan b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 18 May 2015 Received in revised form 2 September 2015 Accepted 4 September 2015 Available online 12 September 2015
Background: Vascular dementia is related to intracranial arteriosclerosis associated with deep white matter lesions (DWMLs). DWMLs have been linked to thrombogenesis due to sustained platelet activation; therefore, an accurate hematological marker is needed. This study was done to evaluate the usefulness of a new method to examine the function of activated platelets in order to assess DWMLs associated with cognitive decline. Methods: A total of 143 individuals (70.4 6.1 years old) who underwent hospital-based health screening using head MRI were evaluated. DWLs were evaluated on T2-weighted and FLAIR images by semiquantitatively grading them from Grade 0 (none) to Grade 3 (severe) using the Fazekas classification. Cognitive function was evaluated using the MMSE and the word fluency test. Platelet activation was assessed using fluorescence-labeled anti-human platelet monoclonal antibodies and semi-quantitatively determining PAC-1- and CD62P-positive rates by flow cytometry. Results: Significant increases in hypertension and CD62P levels were observed with increasing DWML grade (2.6% in Group 0, 3.1% in Group 1, 4.1% in Group 2, and 5.0% in Group 3). CD62P levels were defined as elevated when they were above the mean + 2SD of the Grade 0 group, and the odds ratio of the Grade 2 + 3 group was 3.03. A significant negative correlation was observed between CD62P levels and word fluency tests or the MMSE score. Conclusion: Elevations in CD62P levels, which reflect platelet function activation, were associated with white matter lesions accompanied by a decline in cognitive function. CD62P levels may be useful as a sensitive clinical marker for the early detection of DWMLs with cognitive decline. ã 2015 Elsevier Ireland Ltd. All rights reserved.
Keywords: Deep white matter lesion (DWML) Cognitive decline Platelet activation CD62P
1. Introduction The incidence of vascular dementia has increased recently. An epidemiological study reported that this disease affects 2.5%
* Corresponding author at: Department of Epidemiology for Community Health and Medicine, and Department of Neurology, Kyoto Prefectural University of Medicine, Kyoto 602-8566, Japan. Fax: +81 752515799. E-mail address: [email protected] (N. Kuriyama). http://dx.doi.org/10.1016/j.archger.2015.09.001 0167-4943/ ã 2015 Elsevier Ireland Ltd. All rights reserved.
of people aged over 65 years (Sekita et al., 2010). As an etiological factor, the progression of deep white matter lesions (DWMLs) is known to be closely related to vascular dementia (Gouw et al., 2008; Schmidt et al., 2007). To date, a basic therapy for dementia has not yet been established. With the rapid aging of society, the prevention of DWMLs and their progression may decrease the number of elderly people with cognitive decline, thereby raising an important therapeutic issue (Fazekas et al., 1993; Fernando et al., 2004). However, no
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clinical parameter has yet been identified that can accurately evaluate DWMLs associated with cognitive decline. Cerebral white matter lesions reflect arteriolosclerosis and a chronic reduction in cerebral circulation, and platelet activation may be primarily involved (Fujita & Kawaguchi, 2002; Iwamoto et al., 1995). Chronic hypocirculation involving platelets and hyperaggregability play important roles in the pathogenesis of cerebral infarction, as reported previously (Kuriyama et al., 2010). In clinical practice, antiplatelet drugs that inhibit the functions of platelets have been used to prevent the deterioration of thrombotic arteriosclerotic lesions in the brain, because platelets play the most important role in the pathogenesis of thrombus formation in arteries (Adams et al., 2008; Committee, ESOEE, 2008). However, few studies have investigated whether DWMLs with chronic circulatory disorders and cognitive decline are directly associated with platelet function. Platelets may be activated and aggregate with age, thereby contributing to the progression of arteriosclerosis (Couch & Hassanein, 1976). The importance of a method to accurately evaluate the grade of platelet activation by assessing the level of an antigen that appears on the membrane surface with platelet activation has recently been suggested. Araki et al. (participating in our collaborative study) recently reported that activated platelets that expressed PAC-1 and CD62 were clinically sensitive and important as a marker reflecting the mechanism underlying thrombus formation in arteries (Araki et al., 2009; Shattil et al., 1987). Therefore, the aim of the present study was to clarify whether DWMLs were related to platelet activation as a new evaluation method in a general elderly population using an MRI-based design. Since platelet activation may be an important predictor of the incidence of DWML-related cognitive decline, the expressions of PAC-1 and CD62 on circulating platelets were investigated in patients with various stages of DWMLs, and their relationships with cognitive decline were evaluated. Whether platelet activation was a risk factor for intracranial DWMLs with cognitive decline, as well as their progression, was also examined in a general elderly population.
MMSE Score
2. Materials and methods 2.1. Study subjects A total of 143 participants (86 males, 57 females; 70.4 6.1 years old) who had voluntarily participated in a hospital-based health check-up and underwent brain MRI examinations in 2013 in Kyoto Prefecture were recruited. Subjects with a past or recent history of brain infarction, cardiovascular disease including myocardial infarction, renal failure, or specific neurological disorders such as multiple sclerosis, inflammatory diseases such as systemic lupus erythematosus, or apparent depression and dementia, and those prescribed antiplatelet drugs were excluded from this study. All participants underwent MR evaluations in addition to routine health check-up examinations following a random mailing recruitment approach. One subject dropped out due to the implantation of a pacemaker. The study protocol was approved by the Ethics Committee of our institution, and written, informed consent was obtained from all participating subjects. 2.2. Evaluation of brain MRI Individual brain MRI scans were performed in all subjects using a 1.5-T scanner (Achieva 1.5T, Koninklijke Philips N.V., Eindhoven, The Netherlands), and the findings obtained were evaluated blindly by two board-certified neurologists (N.K., A.T.) and one board-certified radiologist (K.A.). The routine protocol of brain MRI included T1-weighted images (repetition time [TR], 611 ms; echo time [TE], 13 ms), T2-weighted images (TR, 4431 ms; TE, 100 ms), and fluid-attenuated inversion recovery (FLAIR) images (delay time [TI], 2200 ms; TR, 8000 ms; TE, 100 ms). Transverse imaging was performed using 5-mm-thick sections. These protocols were described in our previous MR-based clinical studies (Kuriyama et al., 2014, 2013; Ohshima et al., 2013). In the present study, T2-weighted and FLAIR images were individually assessed to evaluate DWLs, which were graded semiquantitatively from Grade 0 (none) to Grade 3 (severe) according to the Fazekas classification (Fazekas, Chawluk, Alavi, Hurtig, & Zimmerman, 1987). The severity of DWLs was assessed according to the presence of hyperintense lesions in the deep white matter: Grade 0, absent; Grade 1, punctate foci; Grade 2, confluent foci; and Grade 3, extensive confluent foci (Fig. 1). Grade 0–1 DWML was then defined as none/mild DWML, and grade 2–3 DWML was
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Fig. 1. Relationships between platelet expression levels of CD62P and cognitive function scores. The relationship between the expression levels of the surface marker, CD62P, and higher cognitive function was investigated. A negative correlation is observed between CD62P values and MMSE/word fluency test scores (number of correct answers for generated words beginning with “Ta” and animal names) (r = 0.45, 0.51, and 0.48, respectively) (*: all p < 0.05). A significant decrease is observed in MMSE and word fluency scores with an increased percentage of CD62P-expressing platelets (*: p < 0.05).
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defined as marked DWML. Periventricular hyperintensity (PVH) on brain MRI evaluations was also defined according to the de Groot classification (de Groot et al., 2000).
time [s]) is generally assessed by measuring the time that a pulse wave takes to go forth and back between a given distance along a blood vessel and can provide an objective index of atherosclerosis (Lehmann et al., 1998).
2.3. Evaluation of covariates and cognitive function The relationships between various clinical vascular risk factors including% platelet activation were examined in the study group during their visit in 2013 in order to identify the main parameters significantly affecting DWMLs. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) (Folstein, Folstein, & McHugh, 1975). Scores on a 30-point scale were recorded by trained neurologists or a neuropsychologist. MMSE can be universally applied to assess orientation, attention, recall, and language ability, but it is considered insensitive as a global screening test for mild to moderate cognitive impairment. While the MMSE is assumed to assess general cortical cognitive function, a letter fluency test (Cerhan et al., 2002) and word fluency tasks (number of generated words) (Henry, Crawford, & Phillips, 2004; Pasquier, Lebert, Grymonprez, & Petit, 1995) were also performed as representative screening indicators of subcortical cognitive impairments. Subjects were asked to provide as many words beginning with “Ta” as they could recall for the letter fluency task and as many animal names as they could recall for the word fluency task. The scores obtained were the total numbers of correct answers for the generated words in each fluency test. These verbal fluency tasks were administered by trained neuropsychiatric therapists. The cognitive examinations performed on the same day before MR scanning in 2013 were the same as those described in our previous studies (Kuriyama et al., 2014, 2013; Ohshima et al., 2013). Routine peripheral blood and biochemistry examinations were performed as part of the health-screen check-up. Regarding the evaluation of covariates, the classical risk factors examined included: age, sex, HT (systolic blood pressure more than 140 mmHg, diastolic blood pressure more than 90 mmHg; or a history of HT plus antihypertensive medication), diabetes mellitus (DM) (fasting glucose more than 126 mg/dL or treatment with insulin or oral hypoglycemics); hyperlipidemia (HL) (total cholesterol more than 220 mg/dL, low density lipoprotein cholesterol (LDL) more than 140 mg/dL, or treatment with lipid-reducing drugs), and body mass index (BMI; kg/m2). These covariates were obtained during the measurements collected in 2013. In this analysis, a drinker was defined as an individual who had typically been drinking more than 20 g of alcoholic beverages daily for 1 year or longer (Yokoyama, Hiroshi, Ohgo, Hibi, & Saito, 2007). Smoking was also defined as a current smoker who smoked daily, or a former smoker who had quit smoking by the time of this study. These lifestyle factors or behaviors were confirmed using a selfcompleted questionnaire. Since Apoprotein E (APOE) e4 gene is the major known genetic risk factor for cognitive decline, the APOE e4 gene was genotyped, and the number of APOE e4 alleles carried by each subject was determined using commercially available assays (Funakoshi Co., Ltd., Tokyo, Japan). We identified the subjects with the presence of APOE e4 allele as more than one APOE e4 allele (1 APOE e4 allele). Brachial-ankle pulse wave velocity (PWV), a validated noninvasive measurement that represents arterial stiffness, was measured in subjects using a form-I automated PWV/ABI analyzer (Omron Co., Ltd., Kyoto, Japan) attached to the four limbs (Yamashina et al., 2002). The cuffs were wrapped around both upper arms and ankles, with patients resting in the supine position, following a 15-min rest. Pulse volume waveforms at the upper arm and ankle were recorded using a semiconductor pressure sensor. Data are expressed as means standard deviation. Brachial-ankle pulse wave velocity (BaPWV) (=distance [m]/transit
2.4. Whole-blood flow cytometry and quantification of CD62 and PAC1 expression levels Specifically, 2 ml of venous blood were collected in a bloodcollection tube containing acid sodium citrate using a 21-G needle, and they were left for 15 min at room temperature. To avoid spontaneous platelet activation, the first portion of 2 ml was discarded from the blood samples. Then 10 ml of the collected whole blood were transferred to 5 ml of a polystyrene round bottom test tube (BD FalconTM, Catalog Number 352052, Tokyo, Japan), 500 ml of BD Cell FixTM (BD Biosciences, Catalog Number 340181, Tokyo, Japan) were immediately added for fixation, and the mixture was then stored at 4 C until measurement. The resultant platelets were washed with HEPES buffer and resuspended to 4 108 cells/ml for FACS analysis. The FACS was performed within 6 h after blood collection. Platelets were examined for the surface expressions of activated antigens on the platelet membrane, and the percentages of CD62P and PAC-1 expressed by platelets were measured using flow cytometry, as described previously (Araki et al., 2009; Stellos et al., 2010). Specific monoclonal antibodies for CD62P and PAC-1 were used in the quantitative measurement of platelet surface expression. CD62P is an adhesion molecule that belongs to the P-selectin family. It is distributed on the platelet membrane surface with platelet activation, and, thus, is used as a representative marker of platelet activation (Hagberg & Lyberg, 2000). PAC-1 appears at the time of platelet activation-related structural changes in the glycoprotein IIb/IIIa complex on platelets. As PAC-1 expression increases rapidly, even in the presence of weak extra-platelet stimuli, it has been reported as a highly sensitive and specific marker of platelet activation. The platelet surface expression levels of CD62P and PAC-1 were further assessed by whole-blood flow cytometry using a fluorescein isothiocyanate-conjugated PAC-1 antibody and phycoerythrin-conjugated CD62p antibody. A saturating antibody concentration in 50 ml was added to 50 ml of whole blood. Negative control samples contained prepared IgG and IgM. Samples were incubated for 15 min at room temperature and then analyzed within 2 h by flow cytometry. Platelets were identified based on particle size and complexity using a peridimin-chlorophyll-conjugated CD61 antibody and PAC-1 antibody. Fluorescence data from 10,000 platelet events were collected. Expression levels were expressed as a percentage of positively identified platelets. All antibodies were purchased from BD Biosciences (San Jose, CA, USA). 2.5. Statistical analysis Data were analyzed using SPSS Inc., software version 19.0 (SPSS Inc., Chicago, IL, USA). Background factors including sex, age, BMI, and classical vascular risk factors were compared among DWL grade groups using one-way analysis of variance (ANOVA) or the x2 test. Spearman’s rank correlation test was used to assess the relationship between the percentage of activated platelets and cognitive function. The relationships between the parameters associated with the severity of DWMLs were examined using logistic regression analysis. The significance of between-group differences was evaluated using the OR (odds ratio) of the logistic regression analysis. Crude and adjusted (sex, age, HT, DM, HL, PVH, alcohol drinking, smoking, PVH (periventricular hyperintensity), PWV
N. Kuriyama et al. / Archives of Gerontology and Geriatrics 62 (2016) 118–124 Table 1 Clinical characteristics of all subjects.
Age Weight (kg) Height (cm) BMI (kg/m2) Systolic BP (mmHg) Diastolic BP (mmHg) Blood platelet count (104) Hypertension (%) Diabetes mellitus (%) Hyperlipidemia (%) Smoking (%) Alcohol intake (%) Anti-platelet drugs (%)
M SD M SD M SD M SD M SD M SD M SD
Total n = 143
Males n = 86
Females n = 57
70.4 6.1 57.9 10.2 160.2 9.4 22.4 2.7 129.1 15.0 74.5 10.0 21.2 6.1 53 (37.1%) 14 (9.8%) 43 (30.1%) 9 (6.3%) 60 (42.0%) 13 (9.1%)
70.6 5.8 63.2 7.9 165.9 6.1 23.0 2.1 131.0 14.4 77.0 9.1 22.0 7.2 38 (44.2%) 11 (12.8%) 23 (26.7%) 7 (8.1%) 48 (55.8%) 11 (12.8%)
70.0 6.4 49.6 7.4 151.5 6.0 21.7 3.4 125.9 16.7 70.6 10.4 20.8 5.8 15 (26.3%) 3 (5.3%) 20 (35.1%) 2 (3.5%) 12 (21.1 %) 2 (3.5%)
BMI: Body Mass Index; BP: blood pressure; M SD: mean standard deviation.
(pulse wave velocity >1800), the presence of APOE e4 allele, and the use of anti-platelet drugs) ORs with 95% confidence intervals (CIs) were calculated, with p < 0.05 being considered significant. 3. Results The clinical characteristics of the participants in this survey are shown in Table 1; the percentage of HT was higher in males (44.2%) than in females (26.3%), but blood pressure was well controlled in all subjects at the health check-up. No significant differences were observed in the blood platelet count or other platelet-related vascular risk factors between male and female subjects. Regarding the number of cases of each grade, as shown in Table 2, 55 subjects had Grade 0 (mean age 68.4 5.2 years), 55 had Grade 1 (mean age 70.2 5.6 years), 19 had Grade 2 (mean age 74.3 6.4 years), and 14 subjects had Grade 3 (mean age 74.2 7.1 years). Clinical background factors are shown in Table 2
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(upper row). The numbers of patients with hypertension and those with PVH increased significantly with the progression of white matter lesions, that is, with increased grade (p < 0.05). Concerning the other representative arteriosclerosis-associated factors, hypercholesterolemia and diabetes mellitus, no significant increase was observed with increased grade, which differed from the above results. The pulse wave velocity (PWV) was also measured due to the possibility of platelet activation at the peripheral blood vessel level; however, no significant differences were observed among the groups. Regarding the APOE e4 allele, there was no statistical trend for association between the presence of APOE e4 allele and grading of white matter lesions. Regarding the cognitive function tests, the results of grading based on brain MR findings are summarized in Table 2 (lower row). The MMSE and word fluency test scores decreased significantly with the progression of white matter lesions (grade) (p < 0.05). To investigate the relationship between risk factors and PAC-1/ CD62P values in the G0 to G3 groups, to which the subjects were assigned based on brain MR findings, CD62P and PAC-1 values were examined according to the grading of white matter lesions. As shown in Table 2 (lower row), CD62P values were 2.6%, 3.1%, 4.1%, and 5.0% in the G0, G1, G2, and G3 groups, respectively. Thus, this parameter increased significantly with the white matter lesion grade (p < 0.01). On the other hand, the PAC-1 value also increased gradually with the white matter lesion grade; however, no significant differences were observed among the groups, which differed from the results for the CD62P values. Therefore, CD62P was investigated alone in subsequent multivariate analyses. In these multivariate analyses, a mean CD62P value + 2 S.D. (6.1%) of the G0 group or higher was regarded as high. As shown in Table 3, the odds ratio for high CD62P values between 2 groups was calculated, that is, between a group with moderate and severe white matter lesions (the G2 + G3 group) and a group without and with slight white matter lesions (the G0 + G1 group). With respect to high CD62P values, the crude odds ratio in the G2 + G3 group was
Table 2 Clinical characteristics, %CD62 & PAC1-expressing platelets, and cognitive scores by group, and logistic regression analysis of variables in the DWL and DWLP groups.
General clinical characteristics Age (M SD) Hypertension (%) Diabetes mellitus (%) Hyperlipidemia (%) Smoking (%) Alcohol intake (%) HbA1c (%) (M SD) Smoking(%) PWV (m/s) (M SD) PVH (%) 1 ApoE e4 allele. No. (%) Cognitive function score MMSE (M SD) Word fluency animal (M SD) Word fluency TA (M SD)
G0 (n = 55)
G1 (n = 55)
G2 (n = 19)
G3 (n = 14)
p value
68.4 5.2
70.2 5.6
74.3 6.4
74.2 7.1
p = 0.012
16(29.1%) 6(10.9%) 14(25.5%) 4(7.3%) 24(43.6%) 5.7 0.5
22(40.0%) 4(7.3%) 17(30.9%) 3(5.5%) 22(40.0%) 5.8 0.9
7(36.8%) 2(10.5%) 7(36.8%) 1(5.3%) 8(42.1%) 5.9 0.8
8(57.1%) 2(14.3%) 5(35.7%) 1(7.1%) 6(42.9%) 5.6 0.3
p = 0.034* p = 0.895 p = 0.403 p = 0.894 p = 0.769 p = 0.662
3(5.5%) 1328.9 236.2
4(7.3%) 1317.7 216.9
1(5.3%) 1358.9 271.1
1(7.1%) 1331.9 313.1
p = 0.891 p = 0.542
11(20.0%) 6(10.9)
28(50.1%) 5(9.1)
17(89.5%) 2(10.5)
14(100%) 2(14.3)
p = 0.023* p = 0.240
28.9 1.7 17.2 4.8 9.2 3.8
28.1 1.9 16.4 4.4 7.4 2.8
26.7 2.8 15.3 3.4 7.2 2.3
26.4 2.0 14.7 5.1 6.9 3.0
p = 0.032* p = 0.045* p = 0.042*
3.1 1.3 2.9 1.6
4.1 1.5 3.4 1.8
5.0 1.3 3.6 1.4
**
1.1 0.6
1.5 1.3
0.8 0.5
p = 0.402
Quantification of CD62 & PAC1 expressions CD62P (%) (M SD) 2.6 1.0 PAC1 (%) 2.7 1.1 (M SD) 0.9 0.5 PAC1/CD62 (%) (M SD)
p < 0.01 p = 0.059
M SD: mean standard deviation; one-way analysis of variance (ANOVA) for measured values and the chi-square test for the categorical values were used for the analysis. * p < 0.05. ** p < 0.01.
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Table 3 Logistic regression analysis of variables in CD62 & PAC1-expressing platelets in the DWL and DWLP groups. G0 & G1 (n = 110) mild DWLM
G2 & G3 (n = 33) apparent DWML
G2 & G3 (n = 33) apparent DWML
CD62P > 6.1 (%)
3 (2.7)
13 (39.4) Model 1 OR (95% CI)
13 (39.4) Model 2 OR (95% CI)
CD62P > 6.1 (%)
Reference
6.07 (1.3–18.6)*
3.03 (1.8–9.4)*
OR: Odds ratio; CI: confidence interval; Model 1: adjusted by sex and age; Model 2: adjusted by sex, age, hypertension, diabetes mellitus, hyperlipidemia, alcohol drinking, smoking, PVH (periventricular hyperintensity), PWV (pulse wave velocity > 1800), the presence of APOE e4 allele, and anti-platelet drug treatment. * p < 0.05.
6.07 (95% confidence interval (CI): 1.3–18.6) in comparison with the G0 + G1 group. Multiple logistic regression analysis with adjustment for all possible confounding factors was used, because of the potential for bias with the voluntary sample selection. Adjustments were performed for multiple factors, including: sex, age for the DWML group, and other vascular risk factors such as hypertension, hyperlipidemia, diabetes mellitus, alcohol drinking, smoking, PVH (periventricular hyperintensity), high PWV (>1800 = mean + 2SD), the presence of APOE e4 allele, and the presence of antiplatelet drug therapy. The multivariate analysis for high CD62P values showed that the odds ratio in the G2 + G3 group was 3.03 (95% CI: 1.8–9.4) compared with the G0 + G1 group (p < 0.05), even after corrections for these relevant factors. As described above, a correlation was identified between CD62P values and DWML grades. Therefore, whether higher function test parameters were correlated with CD62P values was evaluated. A direct correlation was observed between MMSE scores and CD62P values (correlation coefficient: r = 0.45). Furthermore, there was a negative correlation between CD62P values and word fluency test scores (number of correct answers for generated words beginning with “Ta” and animal names) (r = 0.51, r = 0.48, respectively; both p < 0.05) (Fig. 1). 4. Discussion Sclerosis of arterioles penetrating the cerebral parenchyma accounts for the majority of cerebral white matter lesions, and many factors may be involved in its pathogenesis (Babikian & Ropper, 1987; Fazekas et al., 1993). As factors associated with white matter lesions other than hypertension and aging, previous studies identified diabetes mellitus and hyperlipidemia as vascular risk factors. Epidemiological surveys have also reported relationships between these factors (Breteler et al., 1994; de Leeuw et al., 2002). Our prospective cohort study showed that deep white matter lesions reduced cognitive function. Preventing the progression of white matter lesions represents an important therapeutic strategy for senile dementia (Kuriyama et al., 2013; Vermeer et al., 2003; Enzinger et al., 2007). Raz et al. found that platelet activation, which causes thrombus formation, played an important role in the deterioration of these cerebral white matter lesions, indicating the presence of platelet dysfunction, such as shortening of the platelet lifetime and platelet aggregation related to platelet activation as measured by the expression of glycoprotein IIb/IIIa or enhancement of plateletderived microvesicles (Raz et al., 2013). Furthermore, Fujita et al. (Fujita, Kawaguchi, Uehara, & Fukushima, 2005; Fujita & Kawaguchi, 2002) investigated the relationship between platelet activation and cerebral white matter lesions using a classical platelet aggregation test with adenosine diphosphate (ADP), and
they proposed that enhancement of platelet aggregation was an exacerbating factor. Concerning platelet function, measuring the level of the platelet-specific protein, b-thromboglobulin (bTG), and platelet aggregation tests have been recommended in addition to the above test (Mustard, Moore, Packham, & KinloughRathbone, 1977; Ohkawa et al., 2005). However, these platelet function-testing methods have not yet been standardized; their sensitivity is low, and there are various limitations for clinical use. On the other hand, a flow cytometry method was recently developed to evaluate the grade of platelet activation based on antigen expression on the membrane surface. This method requires a small volume of specimen, and operation methods are simple. Its reproducibility is good, facilitating high-sensitivity measurements. Thus, a new method to evaluate the grade of platelet activation has become available. However, no study has yet examined the brain MR findings of deep cerebral white matter lesions using this method. Araki et al. reported that PAC-1 and CD62 values were sensitive and important markers of platelet activation and reflected the mechanism underlying arterial thrombus formation. Based on this finding, we focused on cognitive decline in the presence of DWMLs and investigated the relationship between PAC-1/CD62 values and MR images/ cognitive function. Platelet aggregation is known to be enhanced in patients with intracerebral arteriosclerotic diseases. A previous study indicated that aging enhanced platelet aggregation, even in healthy adults (Couch & Hassanein, 1976). The present results also identified a relationship between age and the grade of deep cerebral white matter lesions and showed that CD62P values increased with age. As presented in Table 3, adjustments for multiple factors (including age) were performed for the DWML group (G2 + G3 group). The odds ratio for high CD62P values was 3.03 (95% CI: 1.8–9.4), which was significant. Furthermore, a negative correlation was observed between cognitive functions and CD62 values, as shown in Fig. 1. This result suggested that CD62P values were useful as an independent surrogate marker in the deep cerebral white matter lesion group with cognitive decline (DWML group). There have been some studies that found increased platelet expression of Pselectin associated with Alzheimer’s disease (Sevush et al., 1998; Stellos et al., 2010). It is possible that platelet activation also contribute to the pathogenesis of DWMLs associated with cognitive decline. Arteriosclerosis causes hypofunction or injury to vascular endothelial cells (Nabel, 1991). Platelet aggregation is regulated by endothelial cell functions. Therefore, when arteriosclerotic lesions involve an extensive area, the number of activated platelets increases due to endothelial cell hypofunction (Ruggeri, 2003). For example, systemic arteriosclerotic lesions have been detected in a large number of patients with Binswanger's disease, which is a typical disease of intracranial arteriosclerotic lesions (Babikian & Ropper, 1987; Iwamoto et al., 1995). These results indicate that arteriosclerotic lesions involving the whole body may enhance platelet aggregation in patients with severe white matter lesions. Therefore, PWV was measured as an index of systemic arteriosclerosis, and it was found to be slightly higher in the DWML group; however, no significant difference was noted by white matter lesion grade. Adjustments for multiple factors, including sex, age, PWV, and hypertension etc., were performed in the DWML group (G2 + G3 group), and the odds ratio for high CD62P levels was significant. These results suggest that continuous activation of platelets is an independent risk factor which is associated with DWMLs and cognitive decline. It is difficult to define what is meant by continuous platelet activation in this study; however, continuous platelet activation is reflected by platelet microaggregate formation, which is pathophysiologically active and is considered to markedly increase the risk of atherosclerosis and
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atherothrombosis caused by microcirculatory disorders (Ruggeri, 2002). However, one cannot completely rule out the possibility that platelet activation may be secondarily induced. A prospective, longitudinal follow-up survey needs to be performed after 3– 4 years in order to examine the course of DWMLs with high levels of CD62P and cognitive decline. Platelets in blood ejected from the heart pass through perfusion arteries in the brain over a specific period, and they are retained in the intracerebral microcirculation (Adams, 1998). Many platelets interact with vascular endothelial cells in intracerebral blood vessels, and they pass through them in an activation-prone state. Therefore, factors affecting the activation of platelets in circulating blood could include intracerebral microcirculatory disorders, as demonstrated by the present results. These intracerebral microcirculatory disorders may have occurred due to blood–brain barrier hypofunction, as in the DWML group. It has been speculated that the mechanism is mediated by inflammation, such as nitric oxide (NO) or interleukin signaling, as previously reported (Gremmel et al., 2015; Procter et al., 2015). Because Mezger et al. recently reported the correlation between vascular inflammation of the brain and platelets, the present observation could be explained by this kind of inflammatory reaction, and intracerebral microcirculatory disorders can contribute to inflammatory reactions via crosstalk both with immune cells and atherosclerotic endothelial cells in systemic arteriosclerotic arteries or arterioles, including the brain. Further basic evaluation may be needed to clarify this in the future (Mezger et al., 2015). Moreover, whether CD62P values can become a reliable surrogate index of prevention or a therapeutic approach towards DWML with cognitive decline is a next theme to be investigated, taking into consideration the effectiveness of anti-platelet drugs. On the other hand, a previous study suggested that DWMLs associated with cognitive decline are characterized by the release of physiological cognitive function-associated factors, such as beta-amyloid, in addition to a chronic decrease in blood flow (Debette & Markus, 2010). Recently, Marksteiner and Humpel (2013) conducted an in vitro experiment and found that platelets were carriers of beta-amyloid, which reduces cognitive function. Marksteiner and Humpel (2013) recently reported that activated platelets secreted beta-amyloid in Alzheimer patients, and these deposits increased with concomitant cognitive decline. They also reported that circulatory beta-amyloid released from activated platelets was incorporated into atherosclerotic vessels in in vitro systems. These findings implied that the secretion of betaamyloid-containing granule products from platelets may lead to the deposition of beta-amyloid in vascular dementia (Casoli et al., 2007). The present results showed that enhanced CD62-expression by platelets was associated with cognitive decline. Briefly, CD62mediated platelet activation may occur in cerebral white matter lesions with cognitive decline; beta-amyloid may be released by platelets activated in the brain, thus playing an important role in cognitive decline in patients with DWMLs. These changes may be impossible to evaluate using conventional platelet-measuring methods. Whether the level of beta-amyloid derived from platelets in patient serum can be measured in the future (Kitazume et al., 2012) is being reviewed. Moreover, because beta-amyloid is reported to increase from erythrocyte metabolism with aging, the interactions among these hemostatic factors are important as the next targets for our research (Kaminsky et al., 2013; Tikhonova et al., 2014). The present study has two major limitations. One is its relatively small sample size, resulting in insufficient statistical power to assess the hypothesis with a high degree of confidence. To evaluate the diagnostic value of CD62P, a large-scale cohort study is needed. The other limitation of this study is that it currently remains controversial whether platelet activation can be evaluated
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based on the results of a single cross-sectional study alone. Furthermore, the effect of platelet activation on cerebral white matter lesions has yet to be elucidated. To clarify these issues, further studies are needed to investigate whether platelet activation, as confirmed in this pilot study, leads to cognitive decline with the deterioration of cerebral white matter lesions after a few years. Platelet and cognitive functions need to be prospectively and continuously examined over 3 to 4 years, and then we can describe the substantive pattern of the CD62P levels and their effects on cerebral white matter lesions with cognitive decline. In addition, although there was no apparent correlation with APOE 4 allele and cerebral white matter lesions in the present study, we also plan to provide wide genetic profiles in the next health check-up survey, which will be crucial for the interpretation of our results. The pathological feature of CD62P for DWMLs has not yet been clearly defined; however, CD62P may be a clinical marker for the early detection of DWMLs with cognitive decline. We plan to include in our next investigation other useful markers of endothelium-dependent factors (Kosenko et al., 2012), such as NO-containing intermediate products of free radicals, to see if there is some relation with CD62P-related pathological elevations. 5. Conclusion Platelet activation was investigated with respect to the grade of white matter lesions, and its relationship with high CD62P values was confirmed. Furthermore, a direct relationship was observed between high CD62P values and word fluency scores. These results suggest that an increase in CD62P levels, which reflects the activation of platelet function, was associated with white matter lesions in patients with cognitive decline. Thus, conditions that enhance continuous platelet activation with blood-brain barrier hypofunction may be present in cerebral white matter lesions. CD62P values may be useful as a sensitive blood screening marker for cerebral white matter lesions in clinical practice. Conflict of interest The authors have no conflicts of interests. Acknowledgments This work was partially supported by a Grant-in-Aid for Scientific Research (B) (No. 19390178) and Grant-in-Aid for Scientific Research (C) (No. 24590809) from the Ministry of Education, Science, Sports, and Culture of Japan. References Adams, G. (1998). Exercise physiology laboratory manual. New York: W.C.B. McGraw Hill. Adams, R. J., Albers, G., Alberts, M. J., Benavente, O., Furie, K., & Goldstein, L. B., et al., (2008). Update to the AHA/ASA recommendations for the prevention of stroke in patients with stroke and transient ischemic attack. Stroke, 39, 1647–1652. Araki, S., Matsuno, H., Haneda, M., Koya, D., Kanno, Y., & Itho, J., et al., (2009). Correlation between albuminuria and spontaneous platelet microaggregate formation in type 2 diabetic patients. Diabetes Care, 32, 2062–2067. Babikian, V., & Ropper, A. H. (1987). Binswanger’s disease: a review. Stroke, 18, 2–12. Breteler, M. M., van Swieten, J. C., Bots, M. L., Grobbee, D. E., Claus, J. J., & van den Hout, J. H., et al., (1994). Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study. the rotterdam study Neurology, 44, 1246–1252. Casoli, T., Di, S., tefano, G., Giorgetti, B., Grossi, Y., Balietti, M., & Fattoretti, P., et al., (2007). Release of beta-amyloid from high-density platelets: Implications for alzheimer's disease pathology. Annals of the New York Academy of Sciences, 1096, 170–178. Cerhan, J. H., Ivnik, R. J., Smith, G. E., Tangalos, E. C., Petersen, R. C., & Boeve, B. F. (2002). Diagnostic utility of letter fluency, category fluency, and fluency difference scores in alzheimer’s disease. Clinical Neuropsychologist, 16, 35–42.
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