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. Author manuscript; available in PMC: 2010 Sep 1.
Published in final edited form as: Stroke. 2009 Jul 9;40(9):2969–2972. doi: 10.1161/STROKEAHA.109.553339

SELP 1087G/A Polymorphism is Associated with Neuropsychological Test Performance in Older Adults with Cardiovascular Disease

John Gunstad 1,2, Andreana Benitez 1, Karin F Hoth 3, Mary Beth Spitznagel 1,2, Jeanne McCaffery 4, John McGeary 4, Lynn S Kakos 1, Athena Poppas 5, Robert H Paul 6, Angela L Jefferson 7, Lawrence H Sweet 4, Ronald A Cohen 4
PMCID: PMC2752956  NIHMSID: NIHMS139844  PMID: 19590054

Abstract

Background and Purpose

There is growing evidence that the cell adhesion molecule P-selectin (SELP) contributes to the adverse vascular processes that promote cognitive impairment in individuals with cardiovascular disease. Previous research has shown that SELP genotypes moderate circulating levels of P-selectin and that coronary artery bypass graft (CABG) patients with the SELP 1087A allele were less likely to show post-operative cognitive decline and more likely to exhibit lower levels of C-reactive protein (CRP) than non-carriers. Thus, we expected that carriers of the 1087A allele (n = 43) would exhibit better cognitive functioning than persons with two 1087G alleles (n = 77) and that CRP levels would be important for this relationship.

Methods

120 older adults with diagnosed cardiovascular disease (CVD) were recruited from outpatient cardiology clinics. Each participant underwent a comprehensive neuropsychological test battery and a blood draw.

Results

Participants with the SELP 1087A allele performed more poorly on tests of attention [TMT-A: t(116)=3.20, p=.002], executive function [TMT-B: t(116)=2.89, p=.005], psychomotor speed [Digit-Symbol Coding: t(117)=2.54, p=.012], and memory [CVLT Discrimination: t(116)=2.05, p=.04]. There were no significant differences between the SELP genotype groups on demographic/medical variables or CRP levels.

Conclusions

Contrary to expectations, the present analyses showed that older CVD patients with the SELP 1087A allele performed more poorly on neuropsychological testing. Findings from the present study were counter to previous research with CABG candidates. Further work using neuroimaging and alternative measures of cardiovascular function is needed to clarify the mechanisms of this association.

Keywords: P-selectin, Cognitive Function, Heart Disease


Cardiovascular disease (CVD) is a known risk factor for impairments in attention, executive function, memory and other cognitive abilities (13). Numerous physiological consequences associated with CVD are known contributors to these cognitive deficits, including structural damage to the brain, systemic hypoperfusion, and inflammatory processes (47). Recent work suggests that changes in vascular structure and function are an important aspect of cognitive impairment associated with CVD. For example, recent work shows that indices of endothelial function, vascular smooth muscle function, and arterial stiffness are associated with cognitive function (811). Although the exact mechanism has yet to be determined, vascular markers of endothelial function are linked to the development and progression of white matter disease (1213).

There is growing evidence that the cell adhesion molecule P-selectin is an important contributor to the adverse vascular processes that promote cognitive impairment. P-selectin initiates cell activation and adhesion to platelets and endothelial cells, helps to mediate platelet-leukocyte interaction and is expressed following exposure to inflammatory cytokines (1516). Through leukocyte rolling and procoagulation, higher levels of P-selectin promote the development of atherosclerosis and are associated with CVD events (17) and poor neurological outcomes, including greater white matter lesions and ischemic stroke (1819).

In turn, circulating levels of P-selectin are moderated by SELP genotypes (2021), implicating SELP genotypes in the cognitive function of patients with CVD. Consistent with this notion, a recent study directly examined the association between SELP 1087A allele and cognitive function in patients that underwent coronary bypass (22). More specifically, persons with the 1087A minor allele were less likely to show post-operative cognitive decline. Persons with the 1087A allele also exhibited lower levels of C-reactive protein (CRP); the authors raise the possibility that inflammatory processes may be an important contributor to the observed cognitive function (22).

Given the high prevalence of premorbid cognitive dysfunction in candidates for CABG procedures (23), it appears likely that CVD patients that carry the SELP 1087A allele would also have better cognitive function. We examined this possibility in a sample of older adults with CVD who completed a comprehensive neuropsychological test battery and blood draw to determine CRP levels. Based on the above finding, we expected carriers of the 1087A allele would show better cognitive function than carriers of the 1087G allele alone and that CRP levels would be important for this relationship.

Materials and Methods

Participants

Participants were 120 older adults enrolled in a longitudinal examination of the neurocognitive consequences of CVD. Participants for the parent study were recruited from outpatient cardiology clinics and eligible if they had one or more of the following: myocardial infarction, cardiac surgery, heart failure, coronary artery disease, or hypertension. Individuals were excluded from enrolling in the parent study if they had a history of a major neurological disorder (e.g., Alzheimer disease, stroke) or major psychiatric disorder (e.g. schizophrenia, bipolar illness, substance abuse) and thus none were specifically excluded for the current set of analyses. All participants with genotype and CRP data in the parent study were included in the below analyses; no differences emerged between persons that did and did not have these biomarkers in the parent study in key demographic characteristics (e.g. age, p>.93), medical conditions (e.g. myocardial infarction, p>.35) or cognitive function (MMSE; p>.31). Carriers of the 1087A allele were categorized into one group (n = 43) and those with two copies of 1087G (n = 77) were categorized into a second group. Demographic and medical characteristics of SELP groups are presented in Table 1.

Table 1.

Demographic and Medical Characteristics of 120 Older Adults with Cardiovascular Disease

1087G/G (n = 77) 1087G/A or 1087A/A (n = 43) Test Statistic p-value
Demographic Characteristics

 Age, years 69.06 ± 7.53 70.84 ± 8.20 1.20 .23
 Education, years 14.58 ± 2.56 13.73 ± 2.78 1.66 .10
 Female, % 40.2 48.8 0.83 .36
Medical Characteristics (% in each group presenting with specified medical condition)

 Type 2 diabetes, % 21.0 25.6 0.32 .57
 Myocardial infarction, % 44.1 42.8 0.02 .89
 Cardiac Surgery, % 36.4 48.9 1.78 .18
 Hypertension, % 68.8 76.7 0.85 .36
Biomarker
 C-reactive protein 0.20 ± 0.18 0.23 ± 0.17 0.85 .40

Note. No statistically significant differences emerged between groups.

Measures

Neuropsychological Tests

Neuropsychological tests were grouped into one of five neuropsychological domains to facilitate interpretation. Raw scores for each test were used in primary analyses. See Table 2 for neuropsychological test performance. Tests were administered in the following neuropsychological domains:

Table 2.

Neuropsychological Test Performance in 120 Older Adults with Cardiovascular Disease

1087G/G (n = 77) 1087G/A or 1087A/A (n = 43) t-statistic p-value Cohen’s d effect size
Global Function

 Dementia Rating Scale 137.04 ± 4.83 136.56 ± 6.40 0.46 .64 0.08
Attention/Executive/Psychomotor

 Trail Making Test A 36.35 ± 10.42 43.86 ± 15.33 3.20 .002 0.57
 Trail Making Test B 92.64 ± 40.07 119.93 ± 62.59 2.89 .005 0.51
 Controlled Oral Word Association Test 40.84 ± 10.91 36.55 ± 13.60 1.88 .06 0.34
 Digit Symbol Coding 57.61 ± 14.20 50.81 ± 13.60 2.54 .01 0.49
 Digit Span 17.36 ± 3.42 16.84 ± 3.44 0.80 .43 0.15
Learning/Memory

 California Verbal Learning Test: Learning 46.08 ± 12.36 45.30 ± 11.86 0.33 .74 0.06
 California Verbal Learning Test: Short Free Recall 9.04 ± 3.70 8.40 ± 2.83 0.99 .33 0.19
 California Verbal Learning Test: Long Free Recall 9.20 ± 3.84 8.95 ± 3.14 0.36 .72 0.07
 California Verbal Learning Test: Discrimination 92.19 ± 6.94 89.37 ± 7.57 2.05 .04 0.39
Language

 Boston Naming Test 55.15 ± 4.59 53.29 ± 5.66 1.91 .06 0.36
 Animal Naming 19.47 ± 5.52 19.40 ± 5.37 0.07 .95 0.01
Visuospatial

 Block Design 32.77 ± 11.14 29.72 ± 11.03 1.43 .16 0.28
 Hooper Visual Organization Test 23.80 ± 3.42 22.93 ± 3.87 1.25 .21 0.24
Motor
Grooved Pegboard—Dominant 92.47 ± 20.99 101.74 ± 31.73 1.90 .06 0.35
  1. Global Functioning – Dementia Rating Scale (24)

  2. Attention/Executive Function/Psychomotor Speed – Trail Making Test A and B (25), Digit Symbol Coding (26), Controlled Oral Word Association Test (27)

  3. Memory – California Verbal Learning Test learning, short free recall, long free recall, and discrimination (28)

  4. Language – Boston Naming Test (29), Animal Naming (30)

  5. Visual-Spatial – Block Design (26); Hooper Visual Organization Test (31)

  6. Motor – Grooved Pegboard, dominant hand (32)

Procedure

Methods were approved by the local Institutional Review Board and all participants gave written informed consent. Participants provided medical history information through self-report, which was corroborated by medical records wherever possible. Participants then underwent blood draw and completed neuropsychological testing as administered by a trained researcher using standardized instructions. Blood samples were collected in tubes and refrigerated within 10 minutes of collection. Plasma was separated within 4 hours and samples were stored at −70 degrees Celsius until genetic analyses were performed.

All single nucleotide polymorphism (SNP) determinations were performed using the fluorogenic 5′nuclease (Taqman, Applied Biosystems, Foster City, CA) method using reagents (VIC and FAM labeled probes and TaqMan® Universal PCR Master Mix without AMPerase® UNG) obtained from Applied Biosystems (ABI). Reactions were performed in an ABI Prism 7300 Sequence Detection System using both absolute quantification and allelic discrimination modes as described by Livak (1995) and in the accompanying instrument documentation. For rs6131 the Taqman Genotyping assay C-11975296-10 was used.

CRP was determined on a Beckman CX4 autoanalyzer using reagents obtained from Pointe Scientific, Inc (Lincoln Park, MI). The assay range is 0.5–1.0 mg/dl and the interassay coefficient of variation is 2.0%. Laboratory values for the sample appear in Table 1.

Statistical Analysis

The association between SELP genotype and cognitive function was analyzed in several steps. First, the distributions of the primary variables were examined for violations of normality. All distributions were consistent with theoretical models and no variables required transformation. Detailed examination of cognitive tests identified several cases where performance was > ±3 SD from the sample mean. However, Mahalanobis distance analyses indicated no outlier cases and thus no cases were excluded from analyses. Then, t-tests and chi-square analyses were conducted to identify differences in demographic or medical characteristics between the genotype groups for use as covariates in primary analyses. No differences emerged and thus no demographic (e.g. age, gender) or medical covariates (e.g. cardiac surgery, hypertension) were employed (See Table 1). Of note, SELP groups did not differ in CRP levels. Finally, t-tests were conducted to determine differences in neuropsychological test performance across groups.

Results

SELP genotype groups differed on several neuropsychological tests, with medium effect sizes emerging for multiple tests in the attention/executive function/psychomotor speed domain, specifically: Trail Making Test A [t(116) = 3.20, p = .002], Trail Making Test B [t(116) = 2.89, p = .005], and Digit Symbol Coding [t(117) = 2.54, p = .012]. Medium effect sized differences also emerged on a memory index, specifically CVLT Discrimination [t(116) = 2.05, p = .04]. See Table 2. Contrary to expectations, persons with the 1087A allele had poorer neuropsychological test performance for each test.

Discussion

Contrary to expectations and previous work (22), the present analyses showed that older CVD patients with the SELP 1087A allele performed more poorly on several neuropsychological tests assessing attention/executive function/psychomotor speed and a memory index. These medium effect size differences emerged despite SELP genotype groups being similar in demographic and medical conditions. Notably, SELP groups did not differ in CRP levels. Several aspects of these findings warrant brief discussion.

Levels of soluble P-selectin have been associated with increased periventricular white matter lesions (18). As such, it is possible that genetic predispositions to adhesion molecule levels (e.g. P-selectin) and the causative effect of vascular changes on brain lesions may account for the pathophysiology of cognitive difficulties observed in CVD patients. However, the current literature is still in the early stages of identifying which specific polymorphisms predict phenotypes associated with CVD. A comprehensive investigation of genetic correlates of P-selectin in a large community-based study identified specific SELP genotypes that increase or decrease soluble P-selectin, thereby promoting or preventing CVD, respectively (33). Thus, although contrary to findings from previous studies, the current results may illustrate the possible synergistic effects of SELP alleles; the presence of other SELP genotypes may moderate the influence of the SELP 1087A allele, or may interact with the presence of other CVD risk factors, such as hypertension. Further work is needed to clarify this possibility.

An important limitation of the present study is the sole use of the SELP 1087G/A genotype. As noted above, it is not yet entirely clear which genetic polymorphisms predict phenotypes associated with CVD and use of other SELP single nucleotide polymorphisms (SNPs) in isolation or in combination with other genetic factors with known cognitive effects (e.g. ApoE) may produce different results. Similarly, soluble levels of p-selectin were not available as part of this cohort and would help to clarify the unexpected findings. Another potential limitation involves the use of cross sectional methodology, which does not permit examination of the relationship between SELP and cognitive function over time. Given the progressive nature of cognitive decline associated with CVD (34), longitudinal study will be important to investigation of the relationship between SELP genotypes and cognitive function in participants who develop cognitive decline in the future versus those who remain cognitively stable or intact. Further, in light of the known relationship between P-selectin and white matter lesions and ischemic stroke (1819), future studies should also include neuroimaging of cerebrovascular functioning to help clarify possible mechanisms for the relationship between SELP and neuropsychological function. Finally, as the SELP genotype groups did not differ on demographic or medical variables, statistical analyses were not adjusted. However, larger studies are needed to determine whether possible combinations of these variables interact with SELP genotype to influence cognitive test performance.

Summary

Findings from the present study indicate that the SELP 1087G/A SNP is associated with cognitive function in older adults with CVD. Findings were counter to those from candidates for CABG procedures and further work is needed to clarify the mechanisms for this association, particularly prospective studies that include neuroimaging and alternate measures of cerebrovascular function.

References

  • 1.Vogels RL, Oosterman JM, van Harten B, Gouw AA, Schroeder-Tanka JM, Scheltens P, van der Flier WM, Weinstein HC. Neuroimaging and correlates of cognitive function among patients with heart failure. Dement Geriatr Cogn Disord. 2007;24:418–423. doi: 10.1159/000109811. [DOI] [PubMed] [Google Scholar]
  • 2.Solomon A, Kareholt I, Ngandu T, Winblad B, Nissinen A, Tuomilehto J, Soininen H, Kivipelto M. Serum cholesterol changes after midlife and late-life cognition: twenty-one-year follow-up study. Neurology. 2007;68:751–756. doi: 10.1212/01.wnl.0000256368.57375.b7. [DOI] [PubMed] [Google Scholar]
  • 3.Hogue CW, Jr, Hershey T, Dixon D, et al. Preexisting cognitive impairment in women before cardiac surgery and its relationship with C-reactive protein concentrations. Anesth Analg. 2006;102:1602–1608. doi: 10.1213/01.ANE.0000219591.10826.17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Jefferson AL, Poppas A, Paul RH, Cohen RA. Systemic hypoperfusion is associated with executive dysfunction in geriatric cardiac patients. Neurobiol Aging. 2007;28:477–483. doi: 10.1016/j.neurobiolaging.2006.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Jefferson AL, Tate DF, Poppas A, Brickman AM, Paul RH, Gunstad J, Cohen RA. Lower cardiac output is associated with greater white matter hyperintensities in older adults with cardiovascular disease. J Am Geriatr Soc. 2007;55:1044–1048. doi: 10.1111/j.1532-5415.2007.01226.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Gunstad J, Bausserman L, Paul RH, Tate DF, Hoth K, Poppas A, Jefferson AL, Cohen RA. C-reactive protein, but not homocysteine, is related to cognitive dysfunction in older adults with cardiovascular disease. J Clin Neurosci. 2006;13:540–546. doi: 10.1016/j.jocn.2005.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Schram MT, Euser SM, de Craen AJ, Witteman JC, Frolich M, Hofman A, Jolles J, Breteler MM, Westendorp RG. Systemic markers of inflammation and cognitive decline in old age. J Am Geriatr Soc. 2007;55:708–716. doi: 10.1111/j.1532-5415.2007.01159.x. [DOI] [PubMed] [Google Scholar]
  • 8.Moser DJ, Miller IN, Hoth KF, Correia M, Arndt S, Haynes WG. Vascular smooth muscle function is associated with initiation and processing speed in patients with atherosclerotic vascular disease. J Int Neuropsychol Soc. 2008;14:535–541. doi: 10.1017/S1355617708080697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Haley AP, Forman DE, Poppas A, Hoth KF, Gunstad J, Jefferson AL, Paul RH, Ler AS, Sweet LH, Cohen RA. Carotid artery intima-media thickness and cognition in cardiovascular disease. Int J Cardiol. 2007;121:148–152. doi: 10.1016/j.ijcard.2006.10.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Moser DJ, Robinson RG, Hynes SM, Reese RL, Arndt S, Paulsen JS, Haynes WG. Neuropsychological performance is associated with vascular function in patients with atherosclerotic vascular disease. Arterioscler Thromb Vasc Biol. 2007;27:141–146. doi: 10.1161/01.ATV.0000250973.93401.2d. [DOI] [PubMed] [Google Scholar]
  • 11.Fukuhara M, Matsumura K, Ansai T, Takata Y, Sonoki K, Akifusa S, Wakisaka M, Hamasaki T, Fujisawa K, Yoshida A, Fujii K, Iida M, Takehara T. Prediction of cognitive function by arterial stiffness in the very elderly. Circ J. 2006;70:756–761. doi: 10.1253/circj.70.756. [DOI] [PubMed] [Google Scholar]
  • 12.Hoth KF, Tate DF, Poppas A, Forman DE, Gunstad J, Moser DJ, Paul RH, Jefferson AL, Haley AP, Cohen RA. Endothelial function and white matter hyperintensities in older adults with cardiovascular disease. Stroke. 2007;38:308–312. doi: 10.1161/01.STR.0000254517.04275.3f. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Markus HS, Hunt B, Palmer K, Enzinger C, Schmidt H, Schmidt R. Markers of endothelial and hemostatic activation and progression of cerebral white matter hyperintensities: longitudinal results of the Austrian Stroke Prevention Study. Stroke. 2005;36:1410–1414. doi: 10.1161/01.STR.0000169924.60783.d4. [DOI] [PubMed] [Google Scholar]
  • 14.Price JM, Hellermann A, Hellermann G, Sutton ET. Aging enhances vascular dysfunction induced by the Alzheimer’s peptide beta-amyloid. Neurol Res. 2004;26:305–311. doi: 10.1179/016164104225014003. [DOI] [PubMed] [Google Scholar]
  • 15.Ludwig RJ, Schon MP, Boehncke WH. P-selectin: a common therapeutic target for cardiovascular disorders, inflammation and tumour metastasis. Expert Opin Ther Targets. 2007;11:1103–1117. doi: 10.1517/14728222.11.8.1103. [DOI] [PubMed] [Google Scholar]
  • 16.Woollard KJ, Chin-Dusting J. Therapeutic targeting of p-selectin in atherosclerosis. Inflamm Allergy Drug Targets. 2007;6:69–74. doi: 10.2174/187152807780077345. [DOI] [PubMed] [Google Scholar]
  • 17.Varughese GI, Patel JV, Tomson J, Blann AD, Hughes EA, Lip GY. Prognostic value of plasma soluble P-selectin and von Willebrand factor as indices of platelet activation and endothelial damage/dysfunction in high-risk patients with hypertension: a sub-study of the Anglo-Scandinavian Cardiac Outcomes Trial. J Intern Med. 2007;261:384–391. doi: 10.1111/j.1365-2796.2007.01770.x. [DOI] [PubMed] [Google Scholar]
  • 18.de Leeuw FE, de Kleine M, Frijns CJ, Fijnheer R, van Gijn J, Kappelle LJ. Endothelial cell activation is associated with cerebral white matter lesions in patients with cerebrovascular disease. Ann N Y Acad Sci. 2002;977:306–314. doi: 10.1111/j.1749-6632.2002.tb04831.x. [DOI] [PubMed] [Google Scholar]
  • 19.Volcik KA, Ballantyne CM, Coresh J, Folsom AR, Boerwinkle E. Specific P-selectin and P-selectin glycoprotein ligand-1 genotypes/haplotypes are associated with risk of incident CHD and ischemic stroke: the Atherosclerosis Risk in Communities (ARIC) study. Atherosclerosis. 2007;195:e76–82. doi: 10.1016/j.atherosclerosis.2007.03.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Barbaux SC, Blankenberg S, Rupprecht HJ, Francomme C, Bickel C, Hafner G, Nicaud V, Meyer J, Cambien F, Tiret L. Association between P-selectin genetic polymorphisms and soluable P-selectin levels and their relation to coronary artery disease. Arterioscler Thromb Vasc Biol. 2001;21:1668–1673. doi: 10.1161/hq1001.097022. [DOI] [PubMed] [Google Scholar]
  • 21.Carter A, Anagnostopoulou K, Mansfield M, Grant P. Soluble P-selectin levels, P-selectin polymorphisms and cardiovascular disease. J Thromb Haemost. 2003;1:1718–1723. doi: 10.1046/j.1538-7836.2003.00312.x. [DOI] [PubMed] [Google Scholar]
  • 22.Mathew JP, Rinder HM, Smith BR, Newman MF, Rinder CS. Transcerebral platelet activation after aortic cross-clamp release is linked to neurocognitive decline. Ann Thorac Surg. 2006;81:1644–1649. doi: 10.1016/j.athoracsur.2005.12.070. [DOI] [PubMed] [Google Scholar]
  • 23.Vingerhoets G, Van Nooten G, Jannes C. Neuropsychological impairment in candidates for cardiac surgery. J Int Neuropsychol Soc. 1997;3:480–484. [PubMed] [Google Scholar]
  • 24.Mattis S. Dementia Rating Scale (DRS) Odessa, FL: Psychological Assessment Resources; 1998. [Google Scholar]
  • 25.Reitan R. Validity of the trail making test as an indicator of organic brain damage. Percept Mot Skills. 1958;8:271–276. [Google Scholar]
  • 26.Wechsler D. Manual for the Wechsler Adult Intelligence Scale. 3. San Antonio, TX: The Psychological Corporation; 1997. [Google Scholar]
  • 27.Eslinger P, Damasio A, Benton A. The Iowa Screening Battery for Mental Decline. Iowa City, IA: University of Iowa; 1984. [Google Scholar]
  • 28.Delis D, Kramer J, Kaplan E, Ober B. Manual: California Verbal Learning Test, Adult Version. San Antonio, TX: Psychological Corporation; 1987. [Google Scholar]
  • 29.Kaplan E, Goodglass H, Weintraub S. Boston Naming Test. Philadelphia, PA: Lea and Febiger; 1983. [Google Scholar]
  • 30.Morris J, Heyman A, Mohs R, Hughes JP, van Belle G, Fillenbaum G, Mellits ED, Clark C. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurol. 1989;39:1159–1165. doi: 10.1212/wnl.39.9.1159. [DOI] [PubMed] [Google Scholar]
  • 31.Hooper H. The Hooper Visual Organization Test. Los Angeles, CA: Western Psychological Services; 1983. [Google Scholar]
  • 32.Klove H. Clinical neuropsychology. In: Forster FM, editor. The Medical Clinics of North America. New York, NY: Saunders; 1963. [PubMed] [Google Scholar]
  • 33.Lee DS, Larson MG, Lunetta KL, Dupuis J, Rong J, Keaney JF, Lipinska I, Baldwin CT, Vasan RS, Benjamin EJ. Clinical and genetic correlates of soluble P-selectin in the community. J Thromb Haemost. 2008;6:20–31. doi: 10.1111/j.1538-7836.2007.02805.x. [DOI] [PubMed] [Google Scholar]
  • 34.Bruandet A, Richard F, Bombois S, Maurage CA, Deramecourt V, Lebert F, Amouyel P, Pasquier F. Alzheimer disease with cerebrovascular disease and vascular dementia: clinical features and course compared with Alzheimer disease. J Neurol Neurosurg Psychiatry. 2009;30:133–139. doi: 10.1136/jnnp.2007.137851. [DOI] [PubMed] [Google Scholar]

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