Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

C-Reactive protein gene variants are associated with postoperative C-reactive protein levels after coronary artery bypass surgery

  • Tjörvi E Perry1Email author,
  • Jochen D Muehlschlegel1,
  • Kuang-Yu Liu1,
  • Amanda A Fox1,
  • Charles D Collard2,
  • Simon C Body1,
  • Stanton K Shernan1 and
  • the CABG Genomics Investigators
Contributed equally
BMC Medical Genetics200910:38

https://doi.org/10.1186/1471-2350-10-38

Received: 07 August 2008

Accepted: 08 May 2009

Published: 08 May 2009

Abstract

Background

Elevated baseline C-reactive protein (CRP) levels are associated with increased risk for developing cardiovascular disease. Several CRP gene variants have been associated with altered baseline CRP levels in ambulatory populations. However, the influence of CRP gene variants on CRP levels during inflammatory states, such as surgery, is largely unexplored. We describe the association between candidate CRP gene variants and postoperative plasma CRP levels in patients undergoing primary, elective coronary artery bypass graft (CABG) surgery with cardiopulmonary bypass (CPB).

Methods

Using a multicenter candidate gene association study design, we examined the association between seventeen candidate CRP single nucleotide polymorphisms (SNPs) and inferred haplotypes, and altered postoperative CRP levels in 604 patients undergoing CABG surgery with CPB. Perioperative CRP levels were measured immediately prior to surgery, post-CPB and on postoperative days (POD) 1–4.

Results

CRP levels were significantly elevated at all postoperative time points when compared with preoperative levels (P < 0.0001). After adjusting for clinical covariates, the minor allele of the synonymous coding SNP, rs1800947 was associated with lower peak postoperative CRP levels (P = 2.4 × 10-4) and lower CRP levels across all postoperative time points (P = 4.8 × 10-5). rs1800947 remained highly significant after Bonferroni adjustment for multiple comparisons.

Conclusion

We identified a CRP gene SNP associated with lower postoperative CRP levels in patients undergoing CABG surgery with CPB. Further investigation is needed to clarify the significance of this association between CRP gene variants and the acute-phase rise in postoperative CRP levels with regard to the risk of adverse postoperative outcomes.

Background

Human CRP is a highly conserved protein belonging to the pentraxin family of acute phase reactants. Normal baseline plasma CRP levels are ≤1 mg/L in healthy individuals[1]. However, as an acute-phase reactant synthesized in the liver, plasma CRP levels can rise 1000-fold in response to tissue injury or inflammation[2, 3], thereby triggering activation of the classical complement pathway[4, 5], endothelial cell surface adhesion molecule expression[6], leukocyte and macrophage activation, as well as platelet adhesion[1, 7]. The pro-inflammatory effects of CRP may explain the increased risk of developing cardiovascular disease (CVD) associated with persistently elevated baseline CRP levels [812].

Environmental factors such as age, gender, smoking, lipid levels, hypertension and body mass index (BMI) have been shown to influence baseline plasma CRP levels in the absence of overt inflammatory stimuli[8, 13]. Recent family and population-based cohort studies have found moderate heritability of baseline CRP levels [1416]. There is now convincing evidence to support the association between CRP gene variants and baseline plasma CRP levels, and CVD in ambulatory populations [1719]. Furthermore, two recently published genome wide association studies have identified several genes, including the CRP gene, that influence basal CRP levels[20, 21]. However, little is known about the influence of CRP gene variants on the acute-phase response of plasma CRP levels. We therefore examined the association between candidate CRP gene variants and postoperative plasma CRP levels following primary, elective coronary artery bypass graft (CABG) surgery with cardiopulmonary bypass (CPB).

Methods

Study design and population

A candidate gene association study was undertaken to examine the association between CRP gene variants and postoperative plasma CRP levels following CABG surgery with CPB. One thousand eighty-two patients scheduled for primary, elective CABG surgery at the Brigham and Women's Hospital, Boston, MA and the Texas Heart Institute, St Luke's Episcopal Hospital, Houston, TX between August 2001 and June 2007 were eligible for analysis. Following Institutional Review Boards approval, informed consent was obtained from each patient prior to enrollment. Exclusion criteria were defined prior to statistical analysis in order to exclude patients with ongoing preoperative myocardial injury or other acute inflammatory processes that may have confounded the relationship between CRP variants and postoperative CRP level. Exclusion criteria included age <20 years (n = 0), recent (<2 weeks) myocardial infarction (MI) by patient history (n = 207), preoperative white blood cell count >10.0/mm3 (n = 255), preoperative cardiac troponin I (cTnI) level >0.17 ng/mL (n = 220), and recipients of leukocyte-rich blood products within 30 days prior to surgery (n = 15). We excluded eight patients with a preoperative acute inflammatory process and elevated CRP levels (> 60 mg/L).

Study protocol

Preoperative demographic data, environmental risk factors and perioperative surgical and anesthetic management were recorded for all patients. Genomic DNA was isolated from whole blood samples using standard techniques[22]. Plasma CRP concentrations were measured with a competitive format immunoassay, using a monoclonal antibody and labeled CRP, configured on Biosite's Triage device platform (Biosite Inc., San Diego, CA), from plasma drawn at six time points: preoperatively, immediately after termination of CPB, and on the mornings of postoperative days (POD) 1–4. CRP concentrations were calculated using a set of spiked plasma samples as the calibration reference. The analytical sensitivity of the CRP assay is 0.33 μg/mL with precision of 17% over the measurable range of the assay (0.33 – 300 μg/mL).

Candidate SNP identification and genotyping

In an effort to characterize the CRP gene and the surrounding region, we genotyped CRP single nucleotide polymorphisms (SNPs) previously described in the literature[23]. In addition, we genotyped tagging SNPs for the region encompassing the CRP gene including 3000 bp upstream of the transcription start site and 1000 bp downstream of the 3' untranslated region (UTR). Tagging SNPs with minor allele frequencies (MAF) >1% were identified using Tagger based on a pairwise r2 tagging threshold of 0.8 (rs3316653, rs3316654, rs2794517, rs3122012, rs3093058, rs2808630, rs3093077, rs2794520, rs876538, rs876537, rs1572970)[24]. Genotyping was carried out using the iPLEX genotyping platform (Sequenom, San Diego, CA). SNPs that were not in Hardy-Weinberg equilibrium (P = 0.001) or with a MAF <1% were excluded from analysis. Patients with greater than 10% missing genotypes were also excluded. For haplotype association analysis, PHASE version 2.1.1[25, 26] was used to infer common CRP haplotypes (frequency >5%) for every individual.

Statistical analysis

A linear regression model of clinical predictors of postoperative plasma CRP levels was constructed. Clinically relevant variables and those with a P = 0.20 on univariate analysis were entered into the model using stepwise regression. Variables included in the final model were age, gender, race, institution, preoperative CRP level, body mass index (BMI), history of chronic inflammatory disease of the bowel, joints or skin, current smoker, corticosteroid use in the month prior to surgery, HMG-CoA reductase inhibitor use within 24 hours of surgery and administration of a homologous blood product during the perioperative period.

Subsequently, the association between CRP gene variants and rank-ordered peak postoperative CRP levels was tested for dominant, additive and recessive genetic models while adjusting for the variables in the clinical model. To gain additional insight as to how CRP gene variants influence the temporal profile of CRP levels on POD 1–4, CRP measurements were first logit-transformed to approximate a normal distribution – logit-transformation is applied over other forms of transformation to map a bounded variable to the entire real line as is the case with our CRP measurements. Subsequently a repeated-measure Tobit regression model[27], adjusted for the above-mentioned clinical predictors, was applied to estimate the censored normal distribution of the transformed CRP levels while accounting for the correlated observations on different postoperative days for all patients. The repeated-measure Tobit regression model included a random effect to account for the correlation between repeated measures. Finally, robust standard errors were computed based on Huber sandwich estimators to reduce the leverage exerted by any remaining outlier observation in the parameter estimation. Taking into account the posterior probabilities of each possible haplotypic pair, inferred CRP haplotypes were tested for association with CRP levels using the repeated-measure Tobit regression model with the most frequent haplotype (H1) as the reference haplotype. A bootstrapping procedure was applied to estimate the effect of each minor allele or haplotype on postoperative plasma CRP levels, and to mitigate the potential for overfitting[28, 29]. CRP concentrations are presented as medians with inter-quartile ranges. A P < 0.05 after Bonferroni correction was considered statistically significant. SAS version 9.1.3 (SAS Institute, Cary, NC) was used to build the clinical model, R Statistical Software was used for repeated-measure Tobit regression model [30], and PLINK was used for the peak CRP gene association analysis [31].

Results

After implementing the exclusion criteria, 604 of the original 1082 patients were entered into the analysis. Baseline demographic and clinical characteristics are shown in Table 1. Missing pattern analysis on the excluded patients demonstrated no significant differences, and therefore were considered missing at random. The median preoperative plasma CRP level was 1.2 mg/L IQR [0.6–2.8 mg/L]. Postoperative plasma CRP levels were significantly elevated at all time points compared with the preoperative level (P < 0.0001). Median peak postoperative plasma CRP level was 293.3 mg/L IQR [153.6–300.0 mg/L], occurring on POD 2 or 3 in 80.5% of patients. Plasma CRP levels of ≥300 mg/L were measured immediately post-CPB and on PODs 1–4 in 0%, 6.5%, 31.1%, 29.8% and 18.2% of the patients, respectively. Of the nineteen CRP SNPs genotyped, two SNPs (rs3093066 and rs3093058) were excluded for MAFs <1%. The remaining seventeen CRP SNPs survived predefined genotyping quality control criteria, and were included in subsequent analysis. CRP SNPs are characterized in Table 2. The linkage disequilibrium (LD) pattern between genotyped CRP SNPs is shown in Figure 1. All SNPs were in Hardy-Weinberg equilibrium.
Table 1

Baseline demographic and clinical characteristics of the study population (n = 604)*.

Demographic data

Age at enrollment (Yrs)

65 ± 10

Gender (Male %)

82

Race (Caucasian vs. Other %)

89

Institution A, (%)

79

Preoperative Data

 

Body mass index (kg/m2)

28.8 ± 4.9

History of diabetes (Types I and II) (%)

28.5

aHistory of peripheral vascular disease (%)

9.7

bHistory of chronic inflammation (%)

16.8

Current smoker (%)

9.3

cPreoperative CRP level (mg/L)

1.2 [0.6–2.8]

Preoperative creatinine (mg/dL)

1.09 ± 0.30

Preoperative Medications

 

dPreoperative steroid use (%)

2.0

Duration of statin use prior to CABG (%)

 

   No statin use

23.1

   <1 month

11.1

   1–6 months

8.3

   ≥ 6 months

43.6

   Unknown

13.9

Last statin dose administered prior to CABG (%)

 

   <24 hours

62.1

   24–72 hours

5.4

   ≥ 72 hours

1.3

   Unknown

8.1

Preoperative aspirin use (%)

76.3

Intraoperative Data

eBlood product transfusion (%)

56.3

Aortic cross clamp time (min)

73 ± 34

Cardiopulmonary bypass time (min)

98 ± 43

Number of coronary grafts (%)

 

   1

2.8

   2

13.8

   3

44.9

   ≥ 4

38.5

*Continuous data are expressed as mean ± SD. aPeripheral vascular disease was defined as vascular disease of the upper or lower extremities, or thoracic or abdominal aorta by patient history. bChronic inflammation disease of the bowel, joints or skin by patient history. cCRP level expressed in median mg/L with 25th and 75th percentiles.dSteroids given by any route within the last month. eBlood product of any kind given intraoperatively through postoperative day 2.

Table 2

Candidate CRP gene single nucleotide polymorphisms.

dbSNP rs#

Chromosome Position

Nucleotide Position††

Role

Minor:Major Allele

MAF (%)

rs1572970

chr1:157940209

10691

3' Downstream

G:A

0.287

rs876537

chr1:157941557

9343

3' Downstream

T:C

0.393

rs876538

chr1:157942341

8559

3' Downstream

A:G

0.186

rs2794520

chr1:157945440

5460

3' Downstream

T:C

0.337

rs3093077

chr1:157946260

4640

3' Downstream

G:T

0.071

rs2808630

chr1:157947492

3408

3' Downstream

C:T

0.265

rs1205

chr1:157948857

2043

3'UTR

T:C

0.342

rs1130864

chr1:157949715

1185

3'UTR

T:C

0.299

rs3093066

chr1:157949723

1177

3'UTR

A:C

0.009*

rs1800947

chr1:157950062

838

Coding synonymous

C:G

0.071

rs1417938

chr1:157950810

90

Intron

A:T

0.296

rs3091244

chr1:157951289

-390

Promotor

---

0.624 (C)

0.301 (T)

0.075 (A)

rs2794521

chr1:157951720

-821

Promotor

C:T

0.266

rs3093059

chr1:157951760

-861

Promotor

C:T

0.075

rs3093058

chr1:157951939

-1040

Promotor

T:A

0.006*

rs3122012

chr1:157955947

-5048

Promotor

C:T

0.295

rs2794517

chr1:157959329

-8430

Promotor

A:G

0.224

rs3116654

chr1:157962385

-11486

Promotor

C:T

0.123

rs3116653

chr1:157963534

-12635

Promotor

G:C

0.296

NCBI hg version 36. ††Nucleotide position given relative to ATG start codon of the CRP gene. The alleles of the triallelic SNP rs3091244 are described in the MAF column. *Excluded from further analyses due to minor allele frequency (MAF) <1%.

Figure 1

Linkage disequilibrium (LD) pattern for candidate CRP gene single nucleotide polymorphisms (SNPs). NCBI hg version 36. *The triallelic rs3091244 SNP is presented as one base pair apart. Numbers within the pattern represent the r2 values, indicating the level of correlation between single nucleotide polymorphisms. SNPs rs3316653, rs3316654, rs2794517, rs3122012, rs3093058, rs2808630, rs3093077, rs2794520, rs876538, rs876537, and rs1572970 are tagSNPs selected using Haploview's Tagger based on a pairwise r2 tagging threshold of 0.8.

Male gender (P = 0.002), increased BMI (P = 0.046) and perioperative administration of leukocyte-rich blood products (P = 0.02) were independently associated with increased peak postoperative CRP levels based on the clinical regression model. There was no difference in minor allele frequencies or CRP levels between Caucasians and non-Caucasians. After adjusting for clinical covariates, including race, the T allele of rs3091244 was independently associated with higher peak postoperative CRP levels (P = 2.1 × 10-3), while the minor allele (C) of rs1800947 was independently associated with lower peak postoperative CRP levels (P = 2.4 × 10-4) (Table 3). After adjusting for clinical covariates and repeated CRP measurements using Tobit regression analysis, rs3091244 T remained independently associated with higher postoperative CRP levels (P = 2.0 × 10-3) and rs1800947 C was independently associated with lower postoperative CRP levels (P = 4.8 × 10-5) for dominant genetic models (Table 3). Similar model fitting results were found for these SNPs with both dominant and additive genetic models (results not shown). rs1800947 C remained independently associated with lower postoperative CRP levels after adjusting for multiple comparisons. Although rs3091244 T was below the unadjusted level of significance, it achieved only borderline significance after adjusting for multiple comparisons.
Table 3

CRP gene single nucleotide polymorphisms association results for postoperative plasma CRP levels following coronary artery bypass graft surgery.

dbSNP rs#

Minor Allele

β-Coefficient

Peak Postoperative

CRP P-value

Repeated-Measures

Postoperative CRP

P-value††

rs1572970

G

-0.124

0.709

0.180

rs876537

T

-0.107

0.041

0.272

rs876538

A

-0.143

0.606

0.155

rs2794520

T

-0.104

0.004

0.058

rs3093077

G

-0.056

0.931

0.653

rs2808630

C

-0.061

0.898

0.501

rs1205

T

-0.180

0.004

0.068

rs1130864

T

0.232

0.011

9.0 × 10-3

rs1800947

C

-0.477

2.4 × 10-4*

4.8 × 10-5*

rs1417938

C

0.242

0.007

0.006

rs3091244

C

-0.218

0.026

0.105

rs3091244

T

0.274

2.1 × 10-3

2.0 × 10-3

rs3091244

A

-0.075

0.948

0.529

rs2794521

C

-0.059

0.932

0.535

rs3093059

T

-0.067

0.986

0.584

rs3122012

C

0.253

0.009

0.007

rs2794517

A

0.057

0.962

0.555

rs3116654

C

0.014

0.567

0.903

rs3116653

G

0.249

0.008

0.005

Results shown for dominant genetic model. Describes associated effect of the minor allele on postoperative CRP levels based on a Tobit regression model. The same directional effect was seen for peak postoperative CRP levels. Using rank-ordered peak postoperative CRP level adjusted for clinical covariates. ††Using repeated measures of logit-transformed postoperative CRP level in a Tobit regression model and adjusting for clinical covariates. *Below the Bonferroni adjusted level of significance for multiple comparisons.

Four common CRP haplotypes (frequency ≥ 5%) were derived from the two most informative CRP candidate SNPs, rs1800947 and rs3091244, (Table 4). The overall joint test of CRP haplotypes on postoperative CRP levels was highly significant after adjusting for clinical covariates, repeated CRP measurements, and accounting for the posterior probabilities of each possible haplotypic pair (P = 7.44 × 10-8). Compared with the GC haplotype (H1, the most common haplotype), the CC haplotype (H4) was independently associated with lower postoperative CRP levels (P = 4.64 × 10-3) whereas GT haplotype (H2) was associated with higher postoperative CRP levels (P = 0.029).
Table 4

Common CRP haplotypes and association results for altered postoperative CRP levels adjusted for clinical covariates following coronary artery bypass graft surgery.

Haplotypes

rs1800947

rs3091244

Haplotype Frequency

Coefficient

P-value

H1

G

C

0.56

Reference

 

H2

G

T

0.29

0.21*

0.029

H3

G

A

0.07

-0.03

0.771

H4

C

C

0.06

-0.36*

4.64 × 10-3

H Other

--

--

0.02

-0.56

0.808

Results are shown for dominant genetic model. Major and minor alleles, and forward/bottom strand orientation according to NCBI hg version 36 for Caucasian populations. CRP SNPs in strong linkage disequilibrium are combined; therefore not all genotyped SNPs are represented. Describes associated effect of each haplotype on postoperative CRP levels based on a Tobit regression model. Taking into account posterior probabilities, the overall joint test for the haplotype block adjusted for clinical covariates and repeated measures for postoperative CRP was significant at P = 7.44 × 10-8. *The CC haplotype was significantly associated with decreased postoperative CRP levels at P = 4.64 × 10-3 whereas the GT haplotype was associated with increased postoperative CRP levels at P = 0.029.

Observed and bootstrapped estimates of the effects of rs1800947, rs3091244 and H4 on plasma CRP levels (POD1-4) are shown in Figure 2. The rs1800947 minor allele was significantly associated with lower plasma CRP levels on POD2-4 (P ≤ 0.0095), the rs3091244 T allele was significantly associated with higher plasma CRP levels on POD2 and 3 (P ≤ 0.0073), and H4 was associated with lower postoperative plasma CRP levels on POD2-4 (P ≤ 0.0037).
Figure 2

Observed and estimated genetic associations of rs1800947, rs3091244 T and Haplotype 4 with postoperative plasma CRP levels. Box plot results are presented for the dominant genetic model. Dark gray denotes null copy, light gray denotes the minor allele of rs180094, rs3091244 T allele and CC haplotype (H4). Column A. Observed genetic effect on postoperative CRP levels. rs1800947 minor allele and H4 were associated with lower plasma CRP levels (POD2-4 P ≤ 0.0095 and P ≤ 0.0037, respectively), rs3091244 T allele was associated with higher plasma CRP levels (POD2 and 3 P ≤ 0.0073). Column B. Bootstrapping estimates for CRP levels using repeated-measure Tobit regression model adjusted for clinical covariates.

Discussion

We investigated the association between 17 candidate CRP SNPs and perioperative plasma CRP levels in patients undergoing primary, elective CABG surgery with CPB. After adjusting for clinical covariates, the minor allele of the synonymous coding SNP, rs1800947 was associated with lower peak postoperative CRP levels, and lower CRP levels across all postoperative time points. Although the rs3091244 T allele did not survive Bonferroni correction for multiple comparisons, this CRP SNP was strongly associated with elevated postoperative plasma CRP levels following CABG surgery. Furthermore, these associations were not influenced by race. In the largest cardiac surgical cohort study to date to look at CRP polymorphisms, we provide novel evidence that two CRP gene SNPs independently predict postoperative plasma CRP levels following CABG surgery.

The minor allele for the rs1800947 polymorphism has consistently been associated with lower baseline plasma CRP levels[16, 19, 3236] and decreased prevalence of CVD-related mortality in ambulatory populations[18, 37]. However, the association between CRP gene variants and postoperative plasma CRP levels is largely unexplored. Brull et al. sought to test the hypothesis that common CRP gene variants influence both baseline and postoperative plasma CRP levels in patients undergoing CABG surgery[38]. Possibly limited by low statistical power, these authors failed to demonstrate an association between rs1800947 and increased postoperative CRP levels.

Located on exon 2 of the CRP gene, rs1800947 is a synonymous coding polymorphism. Until recently, it has been thought that synonymous coding polymorphisms, such as rs1800947 (CTG [Leu]→CTC [Leu]), do not affect gene function or phenotype. However, recent evidence suggests that allele-specific differences in codons can result in altered post-translational protein folding and function[39, 40]. Nonetheless, without supporting mRNA expression analyses to further elucidate the functional effects of the rs1800947 SNP on plasma CRP levels, we can only speculate as to the functionality of rs1800947. Alternatively, rs1800947 may be in linkage disequilibrium (LD) with a true functional polymorphism; the closest polymorphisms in LD with rs1800947 are rs11265263 (r2 = 0.88) and rs11588887 (r2 = 0.58), 27 kbp and 33.7 kbp in the 5' direction, respectively. Although we were unable to demonstrate significant LD between rs1800947 and other candidate CRP SNPs in this study, more extensive genotyping would be necessary to fully exclude LD with surrounding polymorphisms.

rs3091244 is a tri-allelic SNP located in the promotor region of the CRP gene that has been associated with elevated baseline CRP levels[19, 4144], and increased risk of coronary artery disease (CAD)[18] in ambulatory patients. However, no study to date has examined the association between rs3091244 and postoperative plasma CRP levels. Located in the second of four identified promotor elements (E-box2) in the CRP gene promotor region, Szalai et al. recently demonstrated that rs3091244 affects promotor activity in vitro by altering transcription factor binding sites[45]. Alternatively, rs3091244 may be a marker allele for a true functional CRP gene variant as it is highly correlated with rs3116653, rs3122012, rs1417938 and rs1130864 (r2 ≥ 0.93). Of note, rs3091244 is in strong LD with rs1130864 (r2 ≥ 0.94), the CRP polymorphism described by Brull et al. as having a similar effect on postoperative plasma CRP levels in patients undergoing CABG surgery[38]. Further investigation is warranted to determine the importance of rs3091244 in regulating baseline and possibly the postoperative acute-phase rise plasma CRP levels.

The results of our CRP haplotype analysis are consistent with our SNP analysis findings. Our result suggests that compared with the GC haplotype (H1), the CC haplotype (H4) was significantly associated with decreased postoperative plasma CRP levels and the GT haplotype (H2) with increased CRP levels. Furthermore, the effect size of the CC haplotype (H4) appeared larger than that of the GT haplotype (H2). This would correspond to two independent modifying effects of the rs1800947C (decrease) and rs3091244T (increase) alleles, consistent with the SNP association findings from Table 3 as H4 was tagged by rs1800947C allele and, H2 tagged by the rs3091244T allele. As such, the results of our haplotype analysis add little additional information to our SNP association findings.

Several limitations in this study warrant consideration. Based on a similar study design, we truncated our plasma CRP measurement at 300 mg/L [38]. In an effort to approximate normal distribution, we logit-transformed the left-skewed postoperative CRP distribution, and applied a Tobit regression to recover the truncated CRP levels. Despite estimated median postoperative CRP levels below 300 mg/L in both groups, the effects of CRP gene variants on postoperative plasma CRP levels were large enough to be statistically significant. If we assume that many of the patients with truncated postoperative plasma CRP levels of 300 mg/L in fact had levels greater than 300 mg/L, then our results may in fact underestimate the significance of the association between CRP gene variants and postoperative CRP levels after CABG surgery. Genetic association testing of multiple SNPs to CRP levels at many time points in a large sample population also introduces the potential for false positive findings as a result of multiple testing and over-fitting. After applying the Bonferroni correction to address multiple tests of statistical significance, the rs1800947 remained significantly correlated with altered postoperative plasma CRP levels. While rs3091244 did not survive Bonferroni correction, based on prior studies, we believe its biological significance deserves consideration in future investigations. Inherent bias within the sample population can lead to overfitting and false positive results. Bootstrapping is a statistical re-sampling procedure that alleviates the potential for model overfitting by eliminating bias. Our results show that after applying the bootstrapping procedure, the effect of the genetic variants on postoperative plasma CRP levels remained significantly different, therefore making overfitting unlikely. Finally, recently published results from genome-wide association studies suggest that additional proinflammatory genes (GCKR, HNF1A, LEPR, IL6R, APOE) influence baseline plasma CRP levels in ambulatory populations[20, 21]. It is likely therefore, that a number of genes or a combination thereof, may also influence the acute-phase rise in CRP levels.

Conclusion

Emerging evidence that CRP gene variants associated with elevated baseline plasma CRP levels[16, 32, 36, 41] are heritable [1416]. We submit that the acute-phase rise in postoperative plasma CRP levels after CABG surgery is influenced by CRP gene variants. Further investigation is needed to clarify the significance of the association between CRP gene variants and the acute-phase rise in postoperative CRP levels with regard to the risk of adverse perioperative outcomes.

Notes

Declarations

Acknowledgements

TEP was supported in part by the Scholars in Clinical Science Program, Harvard Medical School K30 RR022292. JDM was supported in part by a Bayer Fellowship in Blood Conservation. SCB was supported in part by a K23 HL68774. We acknowledge the outstanding contributory efforts of the CABG Genomics research staff: James Gosnell, RN; Kujtim Bodinaku, MD; Jai Madan, MD, MPH; Svetlana Gorbatov, MPH; Juliette Dean, RN; James Chen, RN; Jacques Estephan, RN and Isabella Canderlaria, BS.

Authors’ Affiliations

(1)
Brigham and Women's Hospital, Harvard Medical School
(2)
Baylor College of Medicine, Division of Cardiovascular Anesthesia, Texas Heart Institute, St Luke's Episcopal Hospital

References

  1. Armani A, Becker RC: The biology, utilization, and attenuation of C-reactive protein in cardiovascular disease: part I. Am Heart J. 2005, 149 (6): 971-976. 10.1016/j.ahj.2004.12.031.View ArticlePubMedGoogle Scholar
  2. Pepys MB, Hirschfield GM: C-reactive protein: a critical update. J Clin Invest. 2003, 111 (12): 1805-1812.View ArticlePubMedPubMed CentralGoogle Scholar
  3. Agrawal A: CRP after 2004. Mol Immunol. 2005, 42 (8): 927-930. 10.1016/j.molimm.2004.09.028.View ArticlePubMedGoogle Scholar
  4. Kaplan MH, Volanakis JE: Interaction of C-reactive protein complexes with the complement system. I. Consumption of human complement associated with the reaction of C-reactive protein with pneumococcal C-polysaccharide and with the choline phosphatides, lecithin and sphingomyelin. J Immunol. 1974, 112 (6): 2135-2147.PubMedGoogle Scholar
  5. Mold C, Gewurz H, Du Clos TW: Regulation of complement activation by C-reactive protein. Immunopharmacology. 1999, 42 (1–3): 23-30. 10.1016/S0162-3109(99)00007-7.View ArticlePubMedGoogle Scholar
  6. Pasceri V, Willerson JT, Yeh ET: Direct proinflammatory effect of C-reactive protein on human endothelial cells. Circulation. 2000, 102 (18): 2165-2168.View ArticlePubMedGoogle Scholar
  7. Agrawal A, Cha-Molstad H, Samols D, Kushner I: Transactivation of C-reactive protein by IL-6 requires synergistic interaction of CCAAT/enhancer binding protein beta (C/EBP beta) and Rel p50. J Immunol. 2001, 166 (4): 2378-2384.View ArticlePubMedGoogle Scholar
  8. Koenig W, Sund M, Frohlich M, Fischer HG, Lowel H, Doring A, Hutchinson WL, Pepys MB: C-Reactive protein, a sensitive marker of inflammation, predicts future risk of coronary heart disease in initially healthy middle-aged men: results from the MONICA (Monitoring Trends and Determinants in Cardiovascular Disease) Augsburg Cohort Study, 1984 to 1992. Circulation. 1999, 99 (2): 237-242.View ArticlePubMedGoogle Scholar
  9. Mendall MA, Strachan DP, Butland BK, Ballam L, Morris J, Sweetnam PM, Elwood PC: C-reactive protein: relation to total mortality, cardiovascular mortality and cardiovascular risk factors in men. Eur Heart J. 2000, 21 (19): 1584-1590. 10.1053/euhj.1999.1982.View ArticlePubMedGoogle Scholar
  10. Ridker PM, Hennekens CH, Buring JE, Rifai N: C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000, 342 (12): 836-843. 10.1056/NEJM200003233421202.View ArticlePubMedGoogle Scholar
  11. Ridker PM, Buring JE, Shih J, Matias M, Hennekens CH: Prospective study of C-reactive protein and the risk of future cardiovascular events among apparently healthy women. Circulation. 1998, 98 (8): 731-733.View ArticlePubMedGoogle Scholar
  12. Lindahl B, Toss H, Siegbahn A, Venge P, Wallentin L: Markers of myocardial damage and inflammation in relation to long-term mortality in unstable coronary artery disease. FRISC Study Group. Fragmin during Instability in Coronary Artery Disease. N Engl J Med. 2000, 343 (16): 1139-1147. 10.1056/NEJM200010193431602.View ArticlePubMedGoogle Scholar
  13. Mendall MA, Patel P, Ballam L, Strachan D, Northfield TC: C reactive protein and its relation to cardiovascular risk factors: a population based cross sectional study. Bmj. 1996, 312 (7038): 1061-1065.View ArticlePubMedPubMed CentralGoogle Scholar
  14. MacGregor AJ, Gallimore JR, Spector TD, Pepys MB: Genetic effects on baseline values of C-reactive protein and serum amyloid a protein: a comparison of monozygotic and dizygotic twins. Clin Chem. 2004, 50 (1): 130-134. 10.1373/clinchem.2003.028258.View ArticlePubMedGoogle Scholar
  15. Retterstol L, Eikvar L, Berg K: A twin study of C-Reactive Protein compared to other risk factors for coronary heart disease. Atherosclerosis. 2003, 169 (2): 279-282. 10.1016/S0021-9150(03)00192-8.View ArticlePubMedGoogle Scholar
  16. Suk HJ, Ridker PM, Cook NR, Zee RY: Relation of polymorphism within the C-reactive protein gene and plasma CRP levels. Atherosclerosis. 2005, 178 (1): 139-145. 10.1016/j.atherosclerosis.2004.07.033.View ArticlePubMedGoogle Scholar
  17. Chen J, Zhao J, Huang J, Su S, Qiang B, Gu D: -717A>G polymorphism of human C-reactive protein gene associated with coronary heart disease in ethnic Han Chinese: the Beijing atherosclerosis study. J Mol Med. 2005, 83 (1): 72-78. 10.1007/s00109-004-0585-5.View ArticlePubMedGoogle Scholar
  18. Crawford DC, Sanders CL, Qin X, Smith JD, Shephard C, Wong M, Witrak L, Rieder MJ, Nickerson DA: Genetic variation is associated with C-reactive protein levels in the Third National Health and Nutrition Examination Survey. Circulation. 2006, 114 (23): 2458-2465. 10.1161/CIRCULATIONAHA.106.615740.View ArticlePubMedGoogle Scholar
  19. Miller DT, Zee RY, Suk Danik J, Kozlowski P, Chasman DI, Lazarus R, Cook NR, Ridker PM, Kwiatkowski DJ: Association of common CRP gene variants with CRP levels and cardiovascular events. Ann Hum Genet. 2005, 69 (Pt 6): 623-638. 10.1111/j.1529-8817.2005.00210.x.View ArticlePubMedGoogle Scholar
  20. Reiner AP, Barber MJ, Guan Y, Ridker PM, Lange LA, Chasman DI, Walston JD, Cooper GM, Jenny NS, Rieder MJ, et al: Polymorphisms of the HNF1A gene encoding hepatocyte nuclear factor-1 alpha are associated with C-reactive protein. Am J Hum Genet. 2008, 82 (5): 1193-1201. 10.1016/j.ajhg.2008.03.017.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Ridker PM, Pare G, Parker A, Zee RY, Danik JS, Buring JE, Kwiatkowski D, Cook NR, Miletich JP, Chasman DI: Loci related to metabolic-syndrome pathways including LEPR, HNF1A, IL6R, and GCKR associate with plasma C-reactive protein: the Women's Genome Health Study. Am J Hum Genet. 2008, 82 (5): 1185-1192. 10.1016/j.ajhg.2008.03.015.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Collard CD, Shernan SK, Fox AA, Bernig T, Chanock SJ, Vaughn WK, Takahashi K, Ezekowitz AB, Jarolim P, Body SC: The MBL2 'LYQA secretor' haplotype is an independent predictor of postoperative myocardial infarction in whites undergoing coronary artery bypass graft surgery. Circulation. 2007, 116 (11 Suppl): I106-112.PubMedPubMed CentralGoogle Scholar
  23. Hage FG, Szalai AJ: C-reactive protein gene polymorphisms, C-reactive protein blood levels, and cardiovascular disease risk. J Am Coll Cardiol. 2007, 50 (12): 1115-1122. 10.1016/j.jacc.2007.06.012.View ArticlePubMedGoogle Scholar
  24. de Bakker PI, Yelensky R, Pe'er I, Gabriel SB, Daly MJ, Altshuler D: Efficiency and power in genetic association studies. Nat Genet. 2005, 37 (11): 1217-1223. 10.1038/ng1669.View ArticlePubMedGoogle Scholar
  25. Stephens M, Scheet P: Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet. 2005, 76 (3): 449-462. 10.1086/428594.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Stephens M, Smith NJ, Donnelly P: A new statistical method for haplotype reconstruction from population data. Am J Hum Genet. 2001, 68 (4): 978-989. 10.1086/319501.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Imai K, King G, Lau O: Toward A Common Framework for Statistical Analysis and Development. Journal of Computational and Graphical Statistics. 2008, 17 (4): 892-913. 10.1198/106186008X384898.View ArticleGoogle Scholar
  28. Canty A, Ripley B: Boot: Bootstrap R (S-Plus) Functions. Version 1.2–36. 2009Google Scholar
  29. Davison AC, Hinkley DV: Bootstrap Methods and their Application. 1997, New York, NY: Cambridge University PressView ArticleGoogle Scholar
  30. R Development Core Team: R: A Language and Environment for Statistical Computing. 2008, Vienna, Austria: R Foundation for Statistical ComputingGoogle Scholar
  31. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, et al: PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007, 81 (3): 559-575. 10.1086/519795.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Carlson CS, Aldred SF, Lee PK, Tracy RP, Schwartz SM, Rieder M, Liu K, Williams OD, Iribarren C, Lewis EC, et al: Polymorphisms within the C-reactive protein (CRP) promoter region are associated with plasma CRP levels. Am J Hum Genet. 2005, 77 (1): 64-77. 10.1086/431366.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Davey Smith G, Lawlor DA, Harbord R, Timpson N, Rumley A, Lowe GD, Day IN, Ebrahim S: Association of C-reactive protein with blood pressure and hypertension: life course confounding and mendelian randomization tests of causality. Arterioscler Thromb Vasc Biol. 2005, 25 (5): 1051-1056. 10.1161/01.ATV.0000160351.95181.d0.View ArticlePubMedGoogle Scholar
  34. Eklund C, Kivimaki M, Islam MS, Juonala M, Kahonen M, Marniemi J, Lehtimaki T, Viikari J, Raitakari OT, Hurme M: C-reactive protein genetics is associated with carotid artery compliance in men in The Cardiovascular Risk in Young Finns Study. Atherosclerosis. 2008, 196 (2): 841-848. 10.1016/j.atherosclerosis.2007.01.027.View ArticlePubMedGoogle Scholar
  35. Russell AI, Cunninghame Graham DS, Shepherd C, Roberton CA, Whittaker J, Meeks J, Powell RJ, Isenberg DA, Walport MJ, Vyse TJ: Polymorphism at the C-reactive protein locus influences gene expression and predisposes to systemic lupus erythematosus. Hum Mol Genet. 2004, 13 (1): 137-147. 10.1093/hmg/ddh021.View ArticlePubMedGoogle Scholar
  36. Kolz M, Koenig W, Muller M, Andreani M, Greven S, Illig T, Khuseyinova N, Panagiotakos D, Pershagen G, Salomaa V, et al: DNA variants, plasma levels and variability of C-reactive protein in myocardial infarction survivors: results from the AIRGENE study. Eur Heart J. 2008, 29 (10): 1250-1258. 10.1093/eurheartj/ehm442.View ArticlePubMedGoogle Scholar
  37. Lange LA, Carlson CS, Hindorff LA, Lange EM, Walston J, Durda JP, Cushman M, Bis JC, Zeng D, Lin D, et al: Association of polymorphisms in the CRP gene with circulating C-reactive protein levels and cardiovascular events. JAMA. 2006, 296 (22): 2703-2711. 10.1001/jama.296.22.2703.View ArticlePubMedGoogle Scholar
  38. Brull DJ, Serrano N, Zito F, Jones L, Montgomery HE, Rumley A, Sharma P, Lowe GD, World MJ, Humphries SE, 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 (11): 2063-2069. 10.1161/01.ATV.0000084640.21712.9C.View ArticlePubMedGoogle Scholar
  39. Shen LX, Basilion JP, Stanton VP: Single-nucleotide polymorphisms can cause different structural folds of mRNA. Proc Natl Acad Sci USA. 1999, 96 (14): 7871-7876. 10.1073/pnas.96.14.7871.View ArticlePubMedPubMed CentralGoogle Scholar
  40. Kimchi-Sarfaty C, Oh JM, Kim IW, Sauna ZE, Calcagno AM, Ambudkar SV, Gottesman MM: A "silent" polymorphism in the MDR1 gene changes substrate specificity. Science. 2007, 315 (5811): 525-528. 10.1126/science.1135308.View ArticlePubMedGoogle Scholar
  41. Kathiresan S, Larson MG, Vasan RS, Guo CY, Gona P, Keaney JF, Wilson PW, Newton-Cheh C, Musone SL, Camargo AL, et al: Contribution of clinical correlates and 13 C-reactive protein gene polymorphisms to interindividual variability in serum C-reactive protein level. Circulation. 2006, 113 (11): 1415-1423. 10.1161/CIRCULATIONAHA.105.591271.View ArticlePubMedGoogle Scholar
  42. Kovacs A, Green F, Hansson LO, Lundman P, Samnegard A, Boquist S, Ericsson CG, Watkins H, Hamsten A, Tornvall P: A novel common single nucleotide polymorphism in the promoter region of the C-reactive protein gene associated with the plasma concentration of C-reactive protein. Atherosclerosis. 2005, 178 (1): 193-198. 10.1016/j.atherosclerosis.2004.08.018.View ArticlePubMedGoogle Scholar
  43. Suk Danik J, Chasman DI, Cannon CP, Miller DT, Zee RY, Kozlowski P, Kwiatkowski DJ, Ridker PM: Influence of genetic variation in the C-reactive protein gene on the inflammatory response during and after acute coronary ischemia. Ann Hum Genet. 2006, 70 (Pt 6): 705-716. 10.1111/j.1469-1809.2006.00272.x.View ArticlePubMedGoogle Scholar
  44. Wang Q, Hunt SC, Xu Q, Chen YE, Province MA, Eckfeldt JH, Pankow JS, Song Q: Association study of CRP gene polymorphisms with serum CRP level and cardiovascular risk in the NHLBI Family Heart Study. Am J Physiol Heart Circ Physiol. 2006, 291 (6): H2752-2757. 10.1152/ajpheart.01164.2005.View ArticlePubMedGoogle Scholar
  45. Szalai AJ, Wu J, Lange EM, McCrory MA, Langefeld CD, Williams A, Zakharkin SO, George V, Allison DB, Cooper GS, 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 (6): 440-447. 10.1007/s00109-005-0658-0.View ArticlePubMedGoogle Scholar
  46. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/10/38/prepub

Copyright

© Perry et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement