Contribution of clinical correlates and 13 C-reactive protein gene polymorphisms to interindividual variability in serum C-reactive protein level

Genome-wide association with select biomarker traits in the Framingham Heart Study

BACKGROUND

Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations.

METHODS

We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 +/- 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507-1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency > or = 10%, call rate > or = 80% and Hardy-Weinberg equilibrium p > or = 0.001.

RESULTS

With GEE, 58 SNPs had p < 10(-6): the top SNPs were rs2494250 (p = 1.00*10(-14)) and rs4128725 (p = 3.68*10(-12)) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10(-8)) and rs2808629 (p = 3.19*10(-8)) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10(-6): the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10(-8), and rs2494250, p = 3.55*10(-8)), and also included B-type natriuretic peptide (rs437021, p = 1.01*10(-6)) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10(-6)). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.

CONCLUSION

The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.

C-Reactive Protein Gene Polymorphisms, C-Reactive Protein Blood Levels, and Cardiovascular Disease Risk

C-reactive protein (CRP), a blood marker of inflammation and a hallmark of the acute-phase response, has been shown to be a powerful and specific predictor of cardiovascular event risk in populations of otherwise healthy persons. Here we review what is known about CRP gene polymorphisms, discuss how these might affect the epidemiology of CRP and our understanding of CRP's contribution to cardiovascular disease, and examine their potential clinical usefulness. Evidence shows that certain subtle variations in the CRP gene sequence, mostly single nucleotide polymorphisms, predictably and strongly influence the blood level of CRP. Some of these variations are associated with clinical correlates of cardiovascular disease. If future studies can establish with certainty that CRP influences cardiovascular biology, then CRP gene profiling could have clinical utility.

Heritability, Linkage, and Genetic Associations of Exercise Treadmill Test Responses

Background— The blood pressure (BP) and heart rate responses to exercise treadmill testing predict incidence of cardiovascular disease, but the genetic determinants of hemodynamic and chronotropic responses to exercise are largely unknown.

Methods and Results— We assessed systolic BP, diastolic BP, and heart rate during the second stage of the Bruce protocol and at the third minute of recovery in 2982 Framingham Offspring participants (mean age 43 years; 53% women). With use of residuals from multivariable models adjusted for clinical correlates of exercise treadmill testing responses, we estimated the heritability (variance-components methods), genetic linkage (multipoint quantitative trait analyses), and association with 235 single-nucleotide polymorphisms in 14 candidate genes selected a priori from neurohormonal pathways for their potential role in exercise treadmill testing responses. Heritability estimates for heart rate during exercise and during recovery were 0.32 and 0.34, respectively. Heritability estimates for BP variables during exercise were 0.25 and 0.26 (systolic and diastolic BP) and during recovery, 0.16 and 0.13 (systolic and diastolic BP), respectively. Suggestive linkage was found for systolic BP during recovery from exercise (locus 1q43−44, log-of-the-odds score 2.59) and diastolic BP during recovery from exercise (locus 4p15.3, log-of-the-odds score 2.37). Among 235 single-nucleotide polymorphisms tested for association with exercise treadmill testing responses, the minimum nominal probability value was 0.003, which was nonsignificant after adjustment for multiple testing.

Conclusions— Hemodynamic and chronotropic responses to exercise are heritable and demonstrate suggestive linkage to select loci. Genetic mapping with newer approaches such as genome-wide association may yield novel insights into the physiological responses to exercise.

A simple method for the identification of three major haplotypes of the β2AR

We have developed a simple and efficient SSCP (single strand conformational polymorphism) method for haplotype determination of beta2AR using four polymorphisms. The six different SSCP patterns were grouped into three major haplotypes named I, II and III. We studied a population of 199 individuals displaying all the haplotypes: 34.9% (group I), 36.1% (group II) and 29.5% (group III). This population was subdivided into three groups: normal weight, overweight and obese individuals. There were no significant differences between the haplotypes of normal and overweight individuals. The haplotype frequencies in the group of normal weight subjects were 39% (I), 33% (II) and 28% (III). The overweight individuals presented frequencies of 38% (I), 33% (II) and 29% (III). The obese group showed marked differences for haplotypes I and II: 27.1% (I), 43.2% (II) and 29.7% (III) when compared to the normal weight group. For haplotype I the p value of normal to obese groups was 0.0403 with an odds ratio of 0.5761. Our two step SSCP method for beta2AR haplotyping is simple, accurate and cost effective for studying large populations and may be a useful tool for easy and accurate identification of haplotype I which appears to have a protective role against developing obesity.

Atherosclerosis: the path from genomics to therapeutics

Recent rapid advances in genomic tools and techniques hold great promise for transforming the practice of cardiovascular medicine. Resources including the Human Genome Project and the International HapMap project, major technological advances in high-throughput genotyping and methods of statistical analysis, and methods for high-throughput gene expression and small molecule profiling allow researchers to confront issues that will fundamentally change the practice of cardiovascular medicine during the 21st century. Genomic, proteomic, and metabolomic studies of complex cardiovascular diseases such as atherosclerosis will bridge epidemiology and basic biology, and promise increased understanding of cardiovascular disease processes. Genetic approaches applied to atherosclerosis will continue to identify genes and pathways involved in the predisposition to and pathophysiology of atherosclerosis. Gene expression profiling refines our understanding of the dynamic nature of the atherosclerotic vascular wall and promises discovery and validation of targets for therapeutic intervention. Opportunities to translate genetic, genomic, proteomic, and metabolomic information into cardiovascular clinical practice have never been greater, but their fruition requires validation in large independent cohorts, achieved only through collaborative effort. Their continued success will depend on ongoing cooperation within the cardiovascular research community.

Inflammatory biomarkers are associated with total brain volume: the Framingham Heart Study

BACKGROUND

Systemic inflammation is associated with ischemia and Alzheimer disease (AD). We hypothesized that inflammatory biomarkers would be associated with neuroimaging markers of ischemia (i.e., white matter hyperintensities [WMH]) and AD (i.e., total brain volume [TCB]).

METHODS

MRI WMH and TCB were quantified on 1,926 Framingham Offspring participants free from clinical stroke, TIA, or dementia (mean age 60 +/- 9 years; range 35 to 85 years; 54% women) who underwent measurement of a circulating inflammatory marker panel, including CD40 ligand, C-reactive protein, interleukin-6 (IL-6), soluble intracellular adhesion molecule-1, monocyte chemoattractant protein-1, myeloperoxidase, osteoprotegerin (OPG), P-selectin, tumor necrosis factor-alpha (TNFalpha), and tumor necrosis factor receptor II. To account for head size, both TCB (TCBV) and WMH (WMH/TCV) were divided by total cranial volume. We used multivariable linear regression to relate 10 log-transformed inflammatory biomarkers to brain MRI measures.

RESULTS

In multivariable models, inflammatory markers as a group were associated with TCBV (p < 0.0001) but not WMH/TCV (p = 0.28). In stepwise models adjusted for clinical covariates with backwards elimination of markers, IL-6 and OPG were inversely associated with TCBV; TNFalpha was inversely related to TCBV in a subset of 1,430 participants. Findings were similar in analyses excluding individuals with prevalent cardiovascular disease. The relations between TCBV and inflammatory markers were modified by both sex and age, and generally were more pronounced in men and in older individuals.

CONCLUSIONS

Although our observational cross-sectional data cannot establish causality, they are consistent with the hypothesis that higher inflammatory markers are associated with greater atrophy than expected for age.

Identification of a locus modulating serum C-reactive protein levels on chromosome 5p15

OBJECTIVE

Individual propensity to chronic, low-grade inflammation--a determinant of atherosclerosis-is in part under the control of genetic factors. To identify genes involved in this modulation, we performed a 10cM genome screen for linkage with plasma C-reactive protein in 38 extended families including 317 non-diabetic and 177 type 2 diabetic family members (2547 relative pairs).

METHODS AND RESULTS

In a variance component analysis, heritability of CRP values was significant (h(2)=0.39, p<0.0001). This effect was independent of BMI and was present in both diabetic (h(2)=0.42, p=0.003) and non-diabetic (h(2)=0.34, p=0.0015) relatives. The strongest evidence of linkage with CRP was on chromosome 5p15, where the LOD score reached genome-wide significance (LOD=3.41, genome-wide p=0.013). Both diabetic and non-diabetic family members contributed to linkage at this location. Smaller linkage peaks were detected on chromosomes 5q35 (LOD=1.35) and 17p11 (LOD=1.33). When the analysis was restricted to diabetic family members, another peak of moderate intensity (LOD=2.17) was evident at 3p21.

CONCLUSIONS

A major gene influencing CRP levels appears to be located on chromosome 5p15, with an effect that is independent of diabetes. Another gene on 3p21 may control CRP variation but only in the presence of a diabetic or insulin-resistant environment.

β

PURPOSE

This study was designed to illustrate the effects of C-reactive protein (CRP) and interleukin polymorphisms on serum CRP levels.

METHODS

A total of 390 patients with coronary heart disease (CHD) were recruited and high-sensitivity CRP levels were measured. Six polymorphic alleles on the genes of CRP, IL-1, and the IL-1 receptor antagonist were identified. A classification tree was applied to determine their effects and interactions on serum CRP levels.

RESULTS

In the hypertensive CHD patients, the presence of CRP + 1059 GC heterozygotes was associated with a lower risk for elevated CRP levels (OR = 0.318, P = 0.001). The coexistence of CRP + 1059 GC and IL-1beta-511 (CT or TT) might result in reduction in the CRP levels compared to IL-1beta-511 CC (OR = 0.222, P = 0.088 and OR = 0.148, P = 0.060, respectively).

CONCLUSION

The results demonstrated the distribution of CRP-related polymorphisms and the interactions in Taiwanese patients with CHD.

Association study of CRP gene polymorphisms with serum CRP level and cardiovascular risk in the NHLBI Family Heart Study

Recent epidemiological studies have indicated that baseline C-reactive protein (CRP) levels may have value in prediction of cardiovascular risk. Using six tag single-nucleotide polymorphisms (SNPs) selected from our complete list of SNPs on the CRP gene, we investigated the association of CRP genotypes with plasma CRP levels and cardiovascular risk in the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study cohort (1,296 Caucasians, 48.5% male, 54.7 ± 12.8 yr old). There was a significant trend toward association of CRP haplotypes with CRP levels ( P = 0.045). SNP analysis indicated a highly significant association of SNP −757 (rs3093059, P = 0.0004) and SNP −286 (rs3091244, P = 0.0065) and a borderline association of SNP −7180 (rs1341665, P = 0.06) with CRP levels. Neither CRP haplotypes nor individual SNP genotypes were associated with intima-media thickness of the common carotid or internal carotid artery or the bifurcation of the carotid arteries. These results indicated a strong impact of local SNPs of the CRP gene on plasma CRP levels, but there was no direct evidence that these genetically controlled CRP elevations by local CRP SNPs contributed to cardiovascular disease phenotypes.

Genetic variation is associated with C-reactive protein levels in the Third National Health and Nutrition Examination Survey

BACKGROUND

Increased serum C-reactive protein (CRP) is an independent risk factor for cardiovascular disease. Previous studies have suggested that genetic variation within the CRP gene is associated with serum CRP.

METHODS AND RESULTS

We genotyped CRP genetic variants in 7159 individuals from the Third National Health and Nutrition Examination Survey (NHANES III). NHANES III is American population-based sample linked to hundreds of phenotypes, including CRP; however, the CRP assay used in this survey is not a high-sensitivity CRP assay, and 65% of participants (n=4679) had CRP measurements at or below the level of detection. Despite these limitations, we identified specific CRP single-nucleotide polymorphisms (SNPs) and haplotypes associated with serum CRP levels in the general population. Two variants were associated with increased levels of serum CRP: SNP rs3093058 (in linkage disequilibrium with a CRP promoter SNP rs3093062) in the non-Hispanic black sample and the triallelic promoter SNP rs3091244 in the non-Hispanic black and Mexican American samples. Two other SNPs were associated with decreased levels of serum CRP in either the non-Hispanic black (rs1205 and rs2808630) or Mexican American (rs1205) samples. Three haplotypes inferred from 7 SNPs (ATTGCGA, TTAGCGA, and AAAGAGA) were associated (P < or = 0.01) with increased levels of serum CRP in the non-Hispanic black sample; 2 haplotypes (ATTGCGA and AAAGCGA) were associated (P < 0.05) with increased levels in the Mexican American sample; and 1 haplotype (AAAGCGA) was associated (P < 0.03) with increased levels in the non-Hispanic white sample. Post hoc analysis suggests that the AA genotype of the triallelic SNP rs3091244, after adjustment for covariates, was associated with prevalent coronary heart disease in the non-Hispanic white population sample.

CONCLUSIONS

Genetic variation within CRP is associated with serum CRP levels in the general population and may be associated with prevalent coronary heart disease.

Applying pharmacogenomics to enhance the use of biomarkers for drug effect and drug safety

Pharmacogenomics is used to improve patient outcome by maximizing the likelihood of desired effects and minimizing the risk of adverse events using an individual's genetic profile. As such, pharmacogenomics can be used to improve current risk-management strategies (improving the risk-benefit balance). Two areas of great promise for pharmacogenomics in this regard are emerging: (i) the pharmacogenomics of modulating disease biomarkers (to provide insight into novel mechanisms of drug response and to identify the patients most likely to respond to a drug in a favorable way); and (ii) using pharmacogenomics to enhance drug safety. Given that novel biomarkers could enable the earlier detection of many diseases and more-widespread therapies for primary prevention, pharmacogenomics provides the opportunity to identify the patients most likely to respond to these therapies, thereby preserving valuable health-care resources. The use of pharmacogenomics in pharmacovigilance could also be useful for risk-stratifying patients and for helping to identify the mechanisms involved in adverse events.