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J Am Coll Cardiol, 2007; 49:1934-1942, doi:10.1016/j.jacc.2007.01.080 (Published online 30 April 2007).
© 2007 by the American College of Cardiology Foundation
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CLINICAL RESEARCH: CARDIAC SURGERY

Genetic Variants in P-Selectin and C-Reactive Protein Influence Susceptibility to Cognitive Decline After Cardiac Surgery

Joseph P. Mathew, MD*,*, Mihai V. Podgoreanu, MD*, Hilary P. Grocott, MD*, William D. White, MPH*, Richard W. Morris, PhD*, Mark Stafford-Smith, MD*, G. Burkhard Mackensen, MD*, Christine S. Rinder, MD||, James A. Blumenthal, PhD{dagger}, Debra A. Schwinn, MD*,{ddagger},§, Mark F. Newman, MD* for the PEGASUS Investigative Team

* Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina
{dagger} Department of Psychiatry, Duke University Medical Center, Durham, North Carolina
{ddagger} Department of Pharmacology/Cancer Biology, Duke University Medical Center, Durham, North Carolina
§ Duke Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina
|| Departments of Anesthesiology and Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut.

Manuscript received August 25, 2006; revised manuscript received December 6, 2006, accepted January 9, 2007.

* Reprint requests and correspondence: Dr. Joseph P. Mathew, Box 3094, Duke University Medical Center, Durham, North Carolina 27710. (Email: mathe014{at}mc.duke.edu).


   Abstract
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 Abstract
Methods
 Results
 Discussion
 Appendix
 References
 
Objectives: We hypothesized that candidate gene polymorphisms in biologic pathways regulating inflammation, cell matrix adhesion/interaction, coagulation-thrombosis, lipid metabolism, and vascular reactivity are associated with postoperative cognitive deficit (POCD).

Background: Cognitive decline is a common complication of coronary artery bypass graft (CABG) surgery and is associated with a reduced quality of life.

Methods: In a prospective cohort study of 513 patients (86% European American) undergoing CABG surgery with cardiopulmonary bypass, a panel of 37 single-nucleotide polymorphisms (SNPs) was genotyped by mass spectrometry. Association between these SNPs and cognitive deficit at 6 weeks after surgery was tested using multiple logistic regression accounting for age, level of education, baseline cognition, and population structure. Permutation analysis was used to account for multiple testing.

Results: We found that minor alleles of the CRP 1059G/C SNP (odds ratio [OR] 0.37, 95% confidence interval [CI] 0.16 to 0.78; p = 0.013) and the SELP 1087G/A SNP (OR 0.51, 95% CI 0.30 to 0.85; p = 0.011) were associated with a reduction in cognitive deficit in European Americans (n = 443). The absolute risk reduction in the observed incidence of POCD was 20.6% for carriers of the CRP 1059C allele and 15.2% for carriers of the SELP 1087A allele. Perioperative serum C-reactive protein (CRP) and degree of platelet activation were also significantly lower in patients with a copy of the minor alleles, providing biologic support for the observed allelic association.

Conclusions: The results suggest a contribution of P-selectin and CRP genes in modulating susceptibility to cognitive decline after cardiac surgery, with potential implications for identifying populations at risk who might benefit from targeted perioperative antiinflammatory strategies.

Abbreviations and Acronyms
  AA = African American
  CABG = coronary artery bypass graft
  CD62P = P-selectin
  CPB = cardiopulmonary bypass
  CRP = C-reactive protein
  EA = European American
  NA = Native American
  POCD = postoperative cognitive deficit
  SELP = P-selectin gene
  SNP = single-nucleotide polymorphism

Postoperative cognitive dysfunction (POCD), including impairments in attention, memory, language, and processing time, serves as a marker of long-term cognitive decline and is associated with a reduced quality of life despite patients’ expectations that recovery of physical status will generally improve their lives (1). Although many adverse events related to cardiac surgery have been minimized, little progress has been made in reducing POCD, occurring in as many as 53% of patients at hospital discharge and 36% at 6 weeks (2). The etiology of perioperative neurologic injury is multifactorial and includes cerebral embolism and hypoperfusion, but preliminary reports of heritability of cognitive decline (3,4) suggest that genetic factors may also modulate response to this type of neurologic injury. We therefore hypothesized that polymorphisms in candidate genes regulating biologic pathways for inflammation, cell matrix adhesion/interaction, coagulation-thrombosis, lipid metabolism, and vascular reactivity are associated with incidence of POCD after CABG surgery.


   Methods
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 Abstract
 Methods
Results
 Discussion
 Appendix
 References
 
Study population.   Patients enrolled in the study were part of the PEGASUS (Perioperative Genetics and Safety Outcomes Study), an ongoing Institutional Review Board-approved prospective longitudinal study at Duke University Medical Center. The present substudy targeted a cohort of patients undergoing isolated coronary artery bypass graft (CABG) surgery using cardiopulmonary bypass (CPB) between April 1994 and May 2002 in whom detailed genotyping and prospective cognitive testing were performed. Patients were excluded if they had a history of symptomatic cerebrovascular disease, psychiatric illness, renal failure, active liver disease, bleeding disorders, or less than a seventh-grade education.

Measurement of cognitive function phenotype.   Cognitive function was assessed the day before surgery and at 6 weeks after surgery by investigators experienced in neuropsychologic testing and who were blinded to the genetic data. In accordance with the Consensus Statement on Assessment of Neurobehavioral Outcomes After Cardiac Surgery (5), we used a cognitive test battery comprising the following 5 instruments: Short Story module of the Randt Memory Test (6), Modified Visual Reproduction Test from the Wechsler Memory Scale (7), Digit Span subtest of the Wechsler Adult Intelligence Scale-Revised (WAIS-R) exam (8), Digit Symbol subtest of the WAIS-R (8), and the Trail Making Test (Part B) (9).

To account for correlation among cognitive test scores, we performed factor analysis on the 10 cognitive test scores from baseline, as previously described (2). We used SAS Proc Factor (SAS/Genetics version 8.02, SAS Institute, Cary, North Carolina) with a principal components method without priors. Factors were rotated by an orthogonal varimax transformation yielding uncorrelated rotated factors and independent scores representing 4 cognitive domains: 1) verbal memory and language comprehension (short-term and delayed); 2) attention, psychomotor processing speed, and concentration; 3) abstraction and visuospatial orientation; and 4) figural memory. The factor analysis was performed on baseline (preoperative) scores from all eligible patients in our ongoing prospective post-CABG cognitive database (n = 867), of which the patients in the present study were a subset. Factor weights were then used to score the patients in the present study, both at baseline and at 6 weeks. Postoperative cognitive deficit was defined as a decline from baseline score of at least 1 standard deviation for 1 or more of the 4 domain scores at 6 weeks after surgery. Baseline cognitive score was defined as the mean of the 4 preoperative factor scores. A complete description of the factor analysis, including a scree plot and a table of factor loadings, is available in the online .

Candidate gene and polymorphism selection.   A candidate gene set, representing pathways putatively involved in cognitive dysfunction, was selected a priori based on comprehensive analysis of existing expression studies, linkage data, neuropharmacology, population-based association studies, and expert opinion. Principal among these are inflammation, cell matrix adhesion/interaction, thrombosis, lipid metabolism, and vascular reactivity pathways. Preference was given to genes previously implicated in memory, learning, cognition, or mental retardation in both humans and experimental animal models of cognition (10). A panel of 37 specific polymorphisms in these candidate genes was identified from public databases, with emphasis on variants with demonstrated or high likelihood of functionally significant effects (Table 1).


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  		Table 1 Polymorphisms Evaluated for Their Relationship to Cognitive Decline After CABG Surgery
 
Isolation of genomic DNA and genotype analysis.   After isolation of genomic DNA from whole blood, genotyping assays were conducted by matrix assisted laser desorption/ionization time-of-flight mass spectrometry on a Sequenom MassArray system (Sequenom, San Diego, California) at Agencourt Bioscience Corporation (Beverly, Massachusetts). Primers used and polymorphism details are available at: http://anesthesia.duhs.duke.edu/pegasus/cognition/1/cognition-webTable1.htm. Genotyping accuracy of the Sequenom MassArray system was estimated at 99.6% (11). Using direct sequencing on an ABI3700 capillary sequencer (Applied Biosystems, Foster City, California), genotyping reproducibility in this study was validated to be >99% by scoring a panel of 6 polymorphisms in 100 randomly selected patients. The ACE insertion/deletion polymorphism was genotyped by polymerase chain reaction amplification followed by size-fractionation through electrophoresis (12).

Statistical analysis.   Categoric and continuous demographic characteristics were compared between POCD groups with Pearson chi-squared and Wilcoxon rank sum tests, respectively. To test for association between the 37 candidate gene polymorphisms and incidence of POCD, we used a previously described 2-stage analysis approach: marker selection by set association followed by model building (13). This method has been shown to be much more powerful than individual marker analysis when multiple genes are likely involved in a disease phenotype (14).

Allele and genotype frequencies were calculated for each polymorphism, and Hardy-Weinberg equilibrium was evaluated using an exact test. All association analyses were based on 2 genotypic classes, distinguished by the presence or absence of at least 1 copy of the minor allele (homozygote minor and heterozygote versus homozygote major). In the first stage, the set association approach (15) was used to identify a set of markers jointly associated with POCD as follows: Pearson’s chi-square statistics were computed for each of the 37 polymorphisms and ordered from largest to smallest ({chi}1 > {chi}2 > ... {chi}37); sums (si; i = 1, 2, ... , 10) were formed from the 10 largest single-locus statistics; the empirical significance level pi associated with each si was evaluated based on 3,000 random permutations of the data set; the set of markers associated with the smallest pi was selected for further analysis. A series of logistic regression models was then developed to test for association between each pair of markers in the selected set (both as main effects and in interaction) and POCD. Model p values were Bonferroni corrected for multiple comparisons.

To account for covariable effects and population substructure, self-reported ethnicity, age, baseline cognitive score, and years of education were subsequently included in multiple logistic regression modeling. Interactions between genotype and these covariates were also tested. Patients representing ethnic groups other than European American (EA), African American (AA), and Native American (NA) were excluded from analyses involving race. Furthermore, the structured association method was used to control for the possibility of cryptic heterogeneity within the EA patients (16,17); multilocus genotypes from a panel of 52 unlinked bi-allelic null markers, evenly distributed across the genome, were analyzed using Structure version 2.1 software (Division of Biological Sciences, University of Chicago, Chicago, Illinois) to identify clusters of genetically similar individuals. Posterior probabilities of subpopulation membership (based on 2 putative subpopulations) were subsequently used in the logistic regression models that included age, baseline cognitive score, and years of education as covariates.

Haplotypes were inferred from unphased genotypic data using Phase version 2.0 software (Department of Statistics, University of Washington, Seattle, Washington) (18); subsequent haplotype analyses were carried out using Haplo.stats software (Division of Biostatistics, Mayo Clinic, Rochester, Minnesota) (19), restricted to haplotypes with an inferred frequency of >1%. All statistical analyses were performed using SAS and SAS/Genetics version 8.02 (SAS Institute).

Mechanistic subset analyses.   Based on positive genetic associations, platelet activation was measured in a subset of 93 patients for whom serial arterial blood samples had been collected before induction of anesthesia, before aortic cross-clamp release, 10 min after cross-clamp release, at end of CPB, and at end of surgery. After incubation with saturating concentrations of monoclonal antibodies, blood samples were analyzed on a FACScan flow cytometer (Becton-Dickinson, Mountain View, California). The percentage of platelets expressing P-selectin (CD62P) was determined as a marker of platelet activation. Similarly, C-reactive protein (CRP) levels were serially measured in a subset of 239 patients from whom serum had been collected before induction of anesthesia and at 4.5, 24, and 48 h after cross-clamp removal. Immunoassays were forward immunometric assays performed by Biosite Diagnostics (San Diego, California) in 384-well microtiter plates using a Tecan Genesis RSP 200/8 Workstation (Tecan, Research Triangle Park, North Carolina).

The association between percentage of P-selectin–positive platelets and SELP genotype and between serum CRP levels and CRP genotype was tested using repeated measures analysis of variance (ANOVA) based on log transformation and using an unstructured covariance model. Because baseline concentrations differed between SELP genotypes, concentration levels at subsequent times were expressed as ratio to baseline. Genotype differences at individual event times were tested using Wilcoxon rank sum tests when analysis of variance was significant at p < 0.05.


   Results
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Discussion
 Appendix
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Demographic characteristics of the 677 enrolled patients are presented in Table 2. Of these, 164 (24%) did not complete 6-week testing, leaving 513 patients for the final analyses; nonreturners had a lower educational level and total CPB time, were older, and were more likely to suffer from diabetes and pulmonary and vascular disease. Allele frequencies for the single-nucleotide polymorphisms (SNPs) identified below were not different between those who did and did not return for 6-week testing. The incidence of POCD in the study sample was 35.7% (183 out of 513), and patients with a deficit were similar to those without a deficit with the exception of baseline cognition (Table 2).


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  		Table 2 Demographic Characteristics of the Study Population
 
Initial demographic comparisons revealed differences in cognitive deficit among racial groups (EA 34.3%, AA 39.1%, NA 50%) after accounting for age, baseline cognition, and years of education in multivariable logistic regression. Therefore, all subsequent analyses were limited to the subset of EA patients (n = 443). Minor allele frequencies for the 37 polymorphisms examined among the EA patients without cognitive deficit are presented in Table 1. Four polymorphisms had deviations from Hardy-Weinberg equilibrium and were excluded from subsequent analyses.

The marker selection process identified 5 SNPs whose sum of chi-square statistics had a minimum p value of 0.121. Genotype frequencies for these 5 SNPs in patients with and without POCD are presented in Table 3. All 10 possible pairs of 5 SNPs were subjected to logistic regression analysis for association with POCD. The smallest Bonferroni-corrected model p value (p = 0.002) among models with main effects only occurred for SNPs CRP 1059G/C and SELP 1087G/A. This pair of SNPs also had the smallest Bonferroni-corrected model p value (p = 0.005) among models including both main and interaction effects. The interaction effect, however, was not significant (p = 0.425).


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  		Table 3 Genotype Frequencies in European Americans (n = 443) for 5 SNPs Selected for Pair-Wise Modeling
 
Logistic regression in EAs identified age, baseline cognition, and years of education in addition to SNPs CRP 1059G/C and SELP 1087G/A to be significantly associated with POCD (model p < 0.0001) (Table 4). No interaction was found between the SNPs and covariates. Presence of the minor allele at both CRP and SELP polymorphisms had a protective effect; the incidence of cognitive deficit was 16.7% in carriers of minor alleles at both of these loci compared with 42.9% in patients homozygous for the major allele (Fig. 1). Moreover, the absolute risk reduction in the observed incidence of POCD was 20.6% for carriers of the CRP 1059C allele and 15.2% for carriers of the SELP 1087A allele. The CRP and SELP SNPs were not associated with baseline cognition. Detailed analyses of cognitive responses separately by factor and genotype are available in the online and at: http://anesthesia.duhs.duke.edu/pegasus/cognition/1/cognition-webAppendix.htm.


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  		Table 4 Predictors of Cognitive Deficit After Cardiac Surgery in European Americans (n = 443; Area Under the Receiver-Operating Characteristic Curve for This Model Was 0.70)
 

Figure 1
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  		Figure 1 Incidence of Postoperative Cognitive Deficit by CRP 1059G/C and SELP 1087G/A Genotypes

The incidence of cognitive deficit was 16.7% in carriers of minor alleles at both of these loci compared with 42.9% in patients homozygous for the major allele. CRP = C-reactive protein; SELP = P-selectin. n = 386.

 
Pairwise estimates of linkage disequilibrium in EAs between 2 CRP, among 5 SELP SNPs, and between the CRP and SELP SNPs were low, suggesting no strong correlation between the POCD-associated SNPs and other genotyped SNPs. For the CRP gene, containing 2 exons and 1 intron spanning 7 kb, SNPs 1059G/C and 2147C/T exhibited r2 = 0.121 (p < 0.001). For the larger SELP gene, containing 17 exons and 16 introns and spanning >50 kb, r2 values between the POCD-associated SNP 1087G/A, and SNPs 1969A/G, 1902A/G, 2013G/T, and 2361A/C were 0.019, 0.011, 0.019, and 0.008, respectively, with the first and third r2 values significant at p = 0.01. Sixteen unique SELP haplotypes were inferred from the 5 common SELP SNPs, of which 10 exhibited frequencies of >1%. Tests for association between SELP haplotypes and POCD were significant for 2 haplotypes, each bearing the A allele of SELP 1087G/A. These haplotypes had frequencies below 5% and add little to the observed association of SELP 1087G/A to POCD (data not shown).

In separate logistic regression models that included self-reported race in the entire sample, or subpopulation membership probabilities in EAs only, the SNP effects remained significant. However, none of the 2-way interactions between CRP and SELP SNPs with race or subpopulation membership was significant, suggesting that race and population substructure had no effect on the SNP associations described. In non-EAs, the effects of the CRP and SELP SNPs trended toward being protective but were not statistically significant.

For serum CRP levels, a significant interaction between time and CRP 1059G/C genotype was seen (p = 0.011). Serum CRP levels were significantly lower at the 24-hour sampling time in patients homozygous (CC) or heterozygous (CG) for the minor allele compared with patients homozygous (GG) for the major allele (p < 0.001) (Fig. 2). Similarly, a significant genotype and time difference was seen when the effect of the SELP 1087G/A genotype on the percentage of P-selectin–positive platelets was examined. Platelet activation was significantly lower upon release of the cross-clamp (p = 0.043) (Fig. 3) in patients homozygous (A/A) or heterozygous (G/A) for the minor allele compared with patients homozygous (G/G) for the major allele.


Figure 2
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  		Figure 2 Median CRP Levels by CRP 1059G/C Genotypes

C-reactive protein (CRP) levels at the 24-h sampling time in patients homozygous (C/C) or heterozygous (C/G) for the minor allele were lower compared with patients homozygous (G/G) for the major allele. n = 225. *p < 0.05.

 

Figure 3
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  		Figure 3 Median Platelet Activation (Relative to Baseline) by SELP 1087G/A Genotypes

Platelet activation was significantly lower upon release of the cross-clamp in patients with the homozygous minor (A/A) or heterozygous (G/A) genotype compared with patients homozygous (G/G) for the major allele. CPB = cardiopulmonary bypass; SELP = P-selectin. n = 93. *p < 0.05.

 

   Discussion
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 Abstract
 Methods
 Results
 Discussion
Appendix
 References
 
Cognitive dysfunction remains a frequent complication after cardiac surgery, occurring in approximately 36% of patients at 6 weeks after surgery. In the present study of 513 CABG patients tested with a detailed cognitive test battery before and after surgery, we report a potential genetic basis for this cognitive decline. In addition to the previously described risk factors of age, level of education and baseline cognition, we found that the risk of POCD was significantly lower in patients carrying at least 1 copy of the CRP 1059C or SELP 1087A alleles, with an additive effect between loci. Furthermore, we provide preliminary evidence that perioperative serum levels of CRP and platelet activation were reduced in patients with these polymorphisms, providing biologic underpinning to the observed allelic association.

Coronary artery bypass graft surgery using CPB is associated with ischemia-reperfusion injury, inducing a complex inflammatory response that impacts not only the heart but also the brain, lungs, kidneys, and gut (20). C-Reactive protein is an acute-phase reactant produced primarily in the liver in response to tissue injury or inflammation, implicated not only as a marker, but also a potential participant in the pathogenesis of inflammatory-mediated processes (21). Mean CRP concentrations have been reported to rise as much as 83-fold from the preoperative period to 72 h after CABG surgery, and variation in the extent of increase appears to be influenced by CRP genotype (22). Recently, the relationship of patterns of SNP variation at the CRP locus to plasma CRP levels has been extensively characterized in both EA and AA populations (23,24). The synonymous 1059G/C in exon 2 (L184L) has been associated with lower CRP levels in several studies (25–27). Zee and Ridker (26) reported significantly lower CRP levels in G/C heterozygotes than in G/G homozygotes (1.05 vs. 1.38 mg/l); Suk et al. (25) found a 29% lower baseline CRP level in carriers of the minor allele at 1059. Furthermore, 1059G/C is the only SNP that tags a haplotype associated with the lowest plasma CRP levels; in a large population sample 1059G/C decreased plasma CRP an average of 1.5 mg/l/copy (23). Therefore, it is likely that this polymorphism directly influences CRP levels, although the mechanism for a direct effect remains unclear.

The immune system and the central nervous system form a bidirectional communication network. Host defense against infection and recovery from tissue injury includes not only immune activation, but also an integrated neuroendocrine response coordinated by the central nervous system, and several proinflammatory cytokines have been identified as the signaling molecules for immune-to-brain communication (28). In a double-blind crossover study of 20 healthy male volunteers given an intravenous injection of endotoxin, significant positive correlations were found between cytokine secretion and endotoxin-induced decreased verbal and nonverbal memory functions (29). These findings are consistent with reports that memory impairment is a common adverse effect of cytokine therapy and viral infection (30,31). Inflammatory mechanisms and immune activation have been hypothesized to play a role not only in neurodegenerative conditions such as Alzheimer’s disease (32) and vascular dementia (33) but also in age-associated cognitive decline (34–36). Yaffe et al. (36) followed 3,031 well-functioning subjects for 2 years and reported that a high baseline level of serum markers of inflammation, most notably CRP, was associated with poor cognitive performance and greater risk of cognitive decline over the follow-up period. Similar associations between elevated baseline CRP levels and greater cognitive decline have been reported in patients followed for 5 to 6 years (34,35). In the present study, the lower incidence of POCD in patients with the CRP 1059G/C polymorphism may be related to a lesser degree of perioperative inflammation as evidenced by the lower levels of serum CRP.

P-selectin (CD62P) is a membrane glycoprotein that is rapidly mobilized to the surface of activated platelets and endothelial cells where it mediates leukocyte-platelet and leukocyte-vascular endothelial cell adhesion, respectively. Moreover, P-selectin expression on activated platelets appears important for the formation of large stable platelet aggregates and amplification of leukocyte recruitment process (37) and may prime monocytes for tissue factor and cytokine up-regulation (38). In the setting of CPB, activation of platelets, as measured by CD62P expression, peaks 2 to 4 h after CPB and returns to baseline 18 hours after CPB (39). Through increased platelet CD62P expression, CPB results in formation of monocyte-platelet and, to a lesser extent, neutrophil-platelet conjugates (40).

The gene coding for P-selectin (SELP) has been reported to be highly polymorphic (41). The SELP 1087G/A SNP results in a nonsynonymous amino acid change (S290N) in the consensus repeat (sushi) domain; this extracellular domain has been shown to be important for P-selectin binding to its ligand on leukocytes (42,43). In a study of 582 subjects with myocardial infarction (MI) and 630 age-matched control subjects, Tregouet et al. (44) reported that the risk for MI associated with the SELP 1087G/A SNP was reduced but differed according to the haplotype background. In the present study of cardiac surgical patients, we found the 1087G/A variant to be associated with POCD in both genotype and haplotype analyses and provide preliminary evidence for association with lower levels of platelet activation during CPB. Although several studies revealed associations between SELP polymorphisms and soluble P-selectin levels (45,46), which appear highly heritable (47), to our knowledge this is the first report of an association between SELP genotype and P-selectin expression on circulating platelets. However, based on this preliminary data, we cannot rule out that 1087G/A results in altered stability of membrane-bound P-selectin or differential binding of antibodies used for flow cytometry, and further functional characterization of this SNP is required.

When interpreting positive findings from any genetic association study, several epidemiologic limitations should be considered, including inadequate sample size, poorly matched control groups, subgroup analyses, multiple testing, and population stratification (48). With regard to these concerns, strengths of our study include a relatively large sample of cardiac surgery patients (n = 513) who have undergone intensive cognitive evaluation and a prospective cohort design that reduces the selection bias inherent in case-control designs. Although serum CRP and platelet CD62P data were available only for a subset of patients, we were able to provide preliminary evidence of a genotypic effect on both CRP level and platelet activation. However, it is possible that the CRP 1059G/C and SELP 1087G/A SNPs are in linkage disequilibrium with other regulatory (causal) variants not within regions previously scanned for polymorphisms and therefore not included in this study. This is particularly true for the CRP SNP which is silent at the amino acid level. Further, our structured association analysis revealed no evidence of population stratification in these data. Although we did find differences in cognitive deficit among racial groups, we could not detect a genetic effect that differed between races. It is possible that a larger sample of patients with varying ethnicity may have demonstrated such an effect. The definition of "significant" cognitive change, although commonly used, also remains controversial. Our primary aim was to investigate the role of genetic variability in overall postoperative cognitive function rather than specific brain functions and independent constructs. Post hoc analyses using individual factor scores as well as the raw test scores found no significant associations between the CRP and SELP polymorphisms and individual cognitive domains, which may only mean that genetic variations in perioperative inflammatory responses have a broad impact on cortical and subcortical function. Evaluation of other SNPs specifically involved in memory and learning may, however, yield a domain-specific effect.

In summary, using a prospective cohort study design, we found 2 candidate gene polymorphisms with additive effects associated with a reduction in the incidence of cognitive decline after cardiac surgery. Functionally, these CRP and SELP polymorphisms were associated with reductions in serum CRP and platelet activation, respectively, raising the possibility that therapies aimed at reducing the perioperative inflammatory state may be beneficial. Moreover, using cardiac surgery as a model of neurologic injury, these results provide insight into the biologic factors modulating cognitive performance in humans and further evidence for a genetic basis of cognitive deterioration, which should translate into more precise identification of patients at risk.


   Appendix
Top
 Abstract
 Methods
 Results
 Discussion
 Appendix
References
 
For a list of the members of the PEGASUS Investigative Team, and a complete description of the factor analysis, including a scree plot and a table of factor loadings, please see the online version of this article.


   Footnotes
 
Supported in part by grants AG09663 (to Dr. Newman), HL54316 (to Dr. Newman), AG17556 (to Dr. Schwinn), HL075273 (to Dr. Schwinn), and M01-RR-30 (Duke Clinical Research Centers Program) from the National Institutes of Health and grants 0256342U (to Dr. Mathew), 9951185U (to Dr. Mathew), 9970128N (to Dr. Newman), and 0120492U (to Dr. Podgoreanu) from the American Heart Association. Measurement of C-reactive protein levels was supported by Biosite Diagnostics. The first two authors contributed equally to this work. Members of the PEGASUS Investigative Team are acknowledged in the .


   References
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 Methods
 Results
 Discussion
 Appendix
 References
 

  1. Newman MF, Grocott HP, Mathew JP, et al. Report of the substudy assessing the impact of neurocognitive function on quality of life 5 years after cardiac surgery Stroke 2001;32:2874-2881.[Abstract/Free Full Text]
  2. Newman MF, Kirchner JL, Phillips-Bute B, et al. Longitudinal assessment of neurocognitive function after coronary-artery bypass surgery N Engl J Med 2001;344:395-402.[Abstract/Free Full Text]
  3. Lee JH. Genetic evidence for cognitive reserve: variations in memory and related cognitive functions J Clin Exp Neuropsychol 2003;25:594-613.[ISI][Medline]
  4. Potter GG, Plassman BL, Helms MJ, Steffens DC, Welsh-Bohmer KA. Age effects of coronary artery bypass graft on cognitive status change among elderly male twins Neurology 2004;63:2245-2249.[Abstract/Free Full Text]
  5. Murkin JM, Newman SP, Stump DA, Blumenthal JA. Statement of consensus on assessment of neurobehavioral outcomes after cardiac surgery Ann Thorac Surg 1995;59:1289-1295.[Free Full Text]
  6. Randt C, Brown E. Administration Manual: Randt Memory Test. New York, NY: Life Sciences Associates; 1983.
  7. Wechsler D. The Wechsler Memory Scale-Revised (Manual). New York, NY: Psychological Corp; 1987.
  8. Wechsler D. The Wechsler Adult Intelligence Scale-Revised (Manual). New York, NY: Psychological Corp; 1981.
  9. Reitan RM. Validity of the Trail Making Test as an indicator of organic brain damage Percept Mot Skills 1958;8:271-276.[Medline]
  10. Morley KI, Montgomery GW. The genetics of cognitive processes: candidate genes in humans and animals Behav Genet 2001;31:511-531.[CrossRef][ISI][Medline]
  11. Gabriel SB, Schaffner SF, Nguyen H, et al. The structure of haplotype blocks in the human genome Science 2002;296:2225-2229.[Abstract/Free Full Text]
  12. Rigat B, Hubert C, Corvol P, Soubrier F. PCR detection of the insertion/deletion polymorphism of the human angiotensin converting enzyme gene (DCP1) (dipeptidyl carboxypeptidase 1) Nucleic Acids Res 1992;20:1433.[Free Full Text]
  13. Hoh J, Ott J. Mathematical multi-locus approaches to localizing complex human trait genes Nat Rev Genet 2003;4:701-709.[CrossRef][ISI][Medline]
  14. Kim S, Zhang K, Sun F. Detecting susceptibility genes in case-control studies using set association BMC Genet 2003;4(Suppl 1):S9.[CrossRef][Medline]
  15. Wille A, Hoh J, Ott J. Sum statistics for the joint detection of multiple disease loci in case-control association studies with SNP markers Genet Epidemiol 2003;25:350-359.[CrossRef][ISI][Medline]
  16. Pritchard JK, Stephens M, Rosenberg NA, Donnelly P. Association mapping in structured populations Am J Hum Genet 2000;67:170-181.[CrossRef][ISI][Medline]
  17. Cardon LR, Palmer LJ. Population stratification and spurious allelic association Lancet 2003;361:598-604.[CrossRef][ISI][Medline]
  18. Stephens M, Smith NJ, Donnelly P. A new statistical method for haplotype reconstruction from population data Am J Hum Genet 2001;68:978-989.[CrossRef][ISI][Medline]
  19. Lake SL, Lyon H, Tantisira K, et al. Estimation and tests of haplotype-environment interaction when linkage phase is ambiguous Hum Hered 2003;55:56-65.[CrossRef][ISI][Medline]
  20. Herskowitz A, Mangano DT. Inflammatory cascadeA final common pathway for perioperative injury?. Anesthesiology 1996;85:957-960.[CrossRef][ISI][Medline]
  21. Pepys MB, Hirschfield GM. C-reactive protein: a critical update J Clin Invest 2003;111:1805-1812.[CrossRef][ISI][Medline]
  22. Brull DJ, Serrano N, Zito F, et al. Human CRP gene polymorphism influences CRP levels: implications for the prediction and pathogenesis of coronary heart disease Arterioscler Thromb Vasc Biol 2003;23:2063-2069.[Abstract/Free Full Text]
  23. Carlson CS, Aldred SF, Lee PK, et al. Polymorphisms within the C-reactive protein (CRP) promoter region are associated with plasma CRP levels Am J Hum Genet 2005;77:64-77.[CrossRef][ISI][Medline]
  24. Szalai AJ, Wu J, Lange EM, et al. Single-nucleotide polymorphisms in the C-reactive protein (CRP) gene promoter that affect transcription factor binding, alter transcriptional activity, and associate with differences in baseline serum CRP level J Mol Med 2005;83:440-447.[CrossRef][ISI][Medline]
  25. Suk HJ, Ridker PM, Cook NR, Zee RY. Relation of polymorphism within the C-reactive protein gene and plasma CRP levels Atherosclerosis 2005;178:139-145.[CrossRef][ISI][Medline]
  26. Zee RY, Ridker PM. Polymorphism in the human C-reactive protein (CRP) gene, plasma concentrations of CRP, and the risk of future arterial thrombosis Atherosclerosis 2002;162:217-219.[CrossRef][ISI][Medline]
  27. Russell AI, Cunninghame Graham DS, Shepherd C, et al. Polymorphism at the C-reactive protein locus influences gene expression and predisposes to systemic lupus erythematosus Hum Mol Genet 2004;13:137-147.[Abstract/Free Full Text]
  28. Wilson CJ, Finch CE, Cohen HJ. Cytokines and cognition—the case for a head-to-toe inflammatory paradigm J Am Geriatr Soc 2002;50:2041-2056.[CrossRef][ISI][Medline]
  29. Reichenberg A, Yirmiya R, Schuld A, et al. Cytokine-associated emotional and cognitive disturbances in humans Arch Gen Psychiatry 2001;58:445-452.[Abstract/Free Full Text]
  30. Capuron L, Lamarque D, Dantzer R, Goodall G. Attentional and mnemonic deficits associated with infectious disease in humans Psychol Med 1999;29:291-297.[CrossRef][ISI][Medline]
  31. Dantzer R, Wollman EE, Yirmiya R. Cytokines, Stress, and Depression. New York, NY: Kluwer Academic/Plenum; 1999.
  32. Singh VK, Guthikonda P. Circulating cytokines in Alzheimer’s disease J Psychiatr Res 1997;31:657-660.[CrossRef][ISI][Medline]
  33. Schmidt R, Schmidt H, Curb JD, Masaki K, White LR, Launer LJ. Early inflammation and dementia: a 25-year follow-up of the Honolulu-Asia Aging Study Ann Neurol 2002;52:168-174.[CrossRef][ISI][Medline]
  34. Teunissen CE, van Boxtel MP, Bosma H, et al. Inflammation markers in relation to cognition in a healthy aging population J Neuroimmunol 2003;134:142-150.[CrossRef][ISI][Medline]
  35. Tilvis RS, Kahonen-Vare MH, Jolkkonen J, Valvanne J, Pitkala KH, Strandberg TE. Predictors of cognitive decline and mortality of aged people over a 10-year period J Gerontol A Biol Sci Med Sci 2004;59:268-274.[ISI][Medline]
  36. Yaffe K, Lindquist K, Penninx BW, et al. Inflammatory markers and cognition in well-functioning African-American and white elders Neurology 2003;61:76-80.[Abstract/Free Full Text]
  37. Kansas GS. Selectins and their ligands: current concepts and controversies Blood 1996;88:3259-3287.[Free Full Text]
  38. Weyrich AS, McIntyre TM, McEver RP, Prescott SM, Zimmerman GA. Monocyte tethering by P-selectin regulates monocyte chemotactic protein-1 and tumor necrosis factor-alpha secretionSignal integration and NF-kappa B translocation. J Clin Invest 1995;95:2297-2303.[ISI][Medline]
  39. Rinder CS, Mathew JP, Rinder HM, Bonan J, Ault KA, Smith BR. Modulation of platelet surface adhesion receptors during cardiopulmonary bypass Anesthesiology 1991;75:563-570.[ISI][Medline]
  40. Rinder CS, Bonan JL, Rinder HM, Mathew J, Hines R, Smith BR. Cardiopulmonary bypass induces leukocyte-platelet adhesion Blood 1992;79:1201-1205.[Abstract/Free Full Text]
  41. Herrmann SM, Ricard S, Nicaud V, et al. The P-selectin gene is highly polymorphic: reduced frequency of the Pro715 allele carriers in patients with myocardial infarction Hum Mol Genet 1998;7:1277-1284.[Abstract/Free Full Text]
  42. Patel KD, Nollert MU, McEver RP. P-Selectin must extend a sufficient length from the plasma membrane to mediate rolling of neutrophils J Cell Biol 1995;131:1893-1902.[Abstract/Free Full Text]
  43. Ruchaud-Sparagano MH, Malaud E, Gayet O, Chignier E, Buckland R, McGregor JL. Mapping the epitope of a functional P-selectin monoclonal antibody (LYP20) to a short complement-like repeat (SCR 4) domain: use of human-mouse chimaera and homologue-replacement mutagenesis Biochem J 1998;332:309-314.[ISI][Medline]
  44. Tregouet DA, Barbaux S, Escolano S, et al. Specific haplotypes of the P-selectin gene are associated with myocardial infarction Hum Mol Genet 2002;11:2015-2023.[Abstract/Free Full Text]
  45. Barbaux SC, Blankenberg S, Rupprecht HJ, et al. Association between P-selectin gene polymorphisms and soluble P-selectin levels and their relation to coronary artery disease Arterioscler Thromb Vasc Biol 2001;21:1668-1673.[Abstract/Free Full Text]
  46. Carter AM, Anagnostopoulou K, Mansfield MW, Grant PJ. Soluble P-selectin levels, P-selectin polymorphisms and cardiovascular disease J Thromb Haemost 2003;1:1718-1723.[CrossRef][ISI][Medline]
  47. Lee M, Czerwinski SA, Choh AC, et al. Quantitative genetic analysis of cellular adhesion molecules: the FELS longitudinal study Atherosclerosis 2006;185:150-158.[CrossRef][ISI][Medline]
  48. Cardon LR, Bell JI. Association study designs for complex diseases Nat Rev Genet 2001;2:91-99.[CrossRef][ISI][Medline]



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