Epidemiology, Heritability, and Genetic Linkage of C-Reactive Protein in African Americans (from the Jackson Heart Study)

Article Outline

• Abstract
• Methods
• Results
• Discussion
• Acknowledgment
• References
• Copyright

C-reactive protein (CRP) has been studied largely in white non-Hispanic cohorts. There is limited information on CRP's range of values, heritability, and relation to cardiovascular disease risk factors in African Americans. The aim of this study was to evaluate the distribution, clinical correlates, heritability, and genetic linkage of log-transformed CRP in participants in the middle-aged to elderly African American cohort in the community-based Jackson Heart Study. The distribution and correlates of CRP were analyzed for the entire study cohort who underwent the first examination (2001 to 2004). Heritability was estimated for the family cohort nested within the larger Jackson Heart Study (246 families, n = 1,317). The relation between CRP and cardiovascular disease risk factors was tested with multivariable stepwise regression analyses. Heritability was estimated using a variance-components method. Linkage analysis was performed using the multipoint variance-components approach. The study sample consisted of 4,919 participants (mean age 55 ± 13 years, 63% women); the median CRP concentration was 2.7 mg/L. In stepwise models, traditional risk factors explained 23.8% of CRP's variability, with body mass index (partial R² = 13.6%) explaining 57.1% of the variability of CRP due to traditional risk factors. The heritability of CRP (adjusted for age, gender, and body mass index) was 0.45. The strongest linkage evidence for CRP was observed on chromosome 11 (11p13 to 11p11.2), with a logarithm of odds score of 2.72. In conclusion, in this large population-based cohort of African Americans, circulating CRP concentration was heritable and associated with several traditional cardiovascular risk factors, particularly body mass index.

C-reactive protein (CRP) is the inflammatory marker whose relation with cardiovascular disease (CVD) risk factors and CVD has been most intensively studied. CRP concentrations have been correlated with female gender; advancing age¹; diabetes²; higher glucose,² cholesterol,² and triglyceride concentrations; lower high-density lipoprotein³; increasing blood pressure²; smoking²; and body mass index (BMI). Beyond CRP's relation to CVD risk factors, there are numerous investigations supporting an association between CRP and peripheral vascular disease,⁴ ischemic stroke,⁵ and myocardial infarction.⁶ A recent meta-analysis by Danesh et al⁷ examined 7 prospective studies of CRP and long-term coronary artery disease risk with a total of 1,053 events and found an adjusted relative risk of 1.7 for coronary artery disease comparing the top and bottom tertiles of CRP. Given the higher rates of CVD and CVD mortality in African Americans and the relation of CRP to CVD events, the environmental and genetic determinants of CRP in African Americans are of interest. We hypothesized that CRP concentrations are related to CVD risk factors and that there is a significant heritable component after accounting for environmental risk factors. In this study, we evaluated the relation of CRP concentrations to age, gender, and CVD risk factors in the middle-aged to elderly African American cohort of the Jackson Heart Study. We subsequently investigated the heritability of CRP and examined genetic linkage in the family cohort.

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Methods 

The Jackson Heart Study is a longitudinal, population-based, observational cohort that was initiated in 2000 to prospectively investigate the epidemiology and determinants of CVD in African Americans.⁸ Thirty percent of study participants were former members of the Atherosclerosis Risk in Communities (ARIC) study and had been recruited by random selection from the driver's license registry.⁹ Among the remaining participants, 23% were recruited by random selection from the Accudata list, a commercial listing that represents the overall tricounty population. An additional 23% were members of a constrained volunteer sample, in which recruitment was distributed among defined demographic cells in proportions designed to mirror those in the overall population, and 24% were recruited through the Jackson Heart Study Family Study, as described.¹⁰ Among the 5,302 participants recruited for examination 1, a total of 4,919 were used in the analysis performed in this study. The difference of 383 participants was due to a lack of consent for the use of the laboratory data for analysis (n = 23), no CRP values (n = 82), and missing data on covariates used in the various analyses (n = 278). The Jackson Heart Study was approved by the University of Mississippi Medical Center Institutional Review Board, and the participants gave written informed consent.

All clinical covariates were classified at the first examination. BMI was determined as fasting weight divided by height squared; obesity was defined as a BMI ≥30 kg/m². Systolic and diastolic blood pressure were taken in the sitting position by trained technicians using a random-zero sphygmomanometer after 5-minute rest; an average of the second and third readings was used. Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or the reported use of antihypertensive medications <2 weeks before the visit.¹¹ Diabetes mellitus was defined as fasting serum glucose ≥126 mg/dl, the use of diabetic medications within 2 weeks of the clinic visit, or a history of physician-diagnosed diabetes.¹² Insulin resistance was estimated using homeostasis model assessment,¹³ using the following formula: insulin resistance = (fasting plasma insulin [μU/ml]) × (fasting plasma glucose [mmol/L])/22.5. Insulin resistance was defined as a homeostasis model assessment score >4.6 for nondiabetics. Fasting serum total cholesterol and high-density lipoprotein cholesterol and triglyceride concentrations were assessed with Roche enzymatic methods using a Cobras centrifuge analyzer (Hoffman-La Roche, Inc., Nutley, New Jersey), with the laboratory certified by the Lipid Standardization Program of the Centers for Disease Control and Prevention and the National Heart, Lung, and Blood Institute. Prevalent CVD was defined as a stated history of physician-diagnosed myocardial infarction or stroke, electrocardiographic evidence of myocardial infarction, or history of a revascularization procedure (percutaneous transluminal coronary angioplasty, coronary bypass surgery).

CRP was measured in duplicate by the immunoturbidimetric CRP-Latex assay (Kamiya Biomedical Company, Seattle, Washington) using a Hitachi 911 analyzer (Roche Diagnostics, Indianapolis, Indiana), according to the manufacturer's high-sensitivity protocol. The interassay coefficients of variation on control samples repeated in each assay were 4.5% at a CRP concentration of 0.45 mg/L and 4.4% at 1.56 mg/L. Any of the duplicates that were not within 3 assay SDs from one another were rerun. For external quality control (to assess performance at the clinical center and in the laboratory), approximately 6% of samples were measured as masked replicates on different dates to assess the repeatability of measurements of CRP. The reliability coefficient for masked quality control replicates was 0.95 for the CRP assay.

Genotyping was performed by the Mammalian Genotyping Service (National Heart, Lung, and Blood Institute, Bethesda, Maryland; http://research.marshfieldclinic.org/genetics). A total of 1,501 subjects were genotyped for 374 polymorphic markers (Marshfield marker set 16). Average heterozygosity was 0.76, and the gender-averaged mean intermarker spacing was 9.3 cM. After extensive quality checks to verify the consistency of marker genotyping and stated pedigree relations, a total of 246 families (1,317 subjects) were included in the final genetic analysis data set.¹⁰

We obtained descriptive statistics to determine the means, SDs, and/or percentages for study participants' characteristics. Frequency distributions were used for categorical data. Descriptive statistics were also used to determine the mean, median, SD, 25th percentile, and 75th percentile of CRP by age and gender in the study population. Similar descriptive analysis was performed for the family sample. To establish reference ranges for CRP concentrations in African Americans, a reference sample was selected from the study population. The reference sample excluded participants with CRP concentrations >10 mg/L, hypertension, diabetes, obesity, chronic kidney disease (defined as estimated glomerular filtration rate <60 ml/min/1.73 m²), or prevalent CVD and excluded participants taking lipid-lowering and hormone replacement therapy. The reference sample was compared with the broad sample, consisting of all other participants and with the family sample.

Because its distribution was skewed, CRP concentration was log-transformed for clinical correlates and genetic analyses.¹⁴ Age- and gender-adjusted linear regression was used to assess the relation of traditional cardiovascular risk factors to CRP concentrations (dependent variable). We performed stepwise linear regression (p <0.05 to remain in the model) with age and gender forced in to determine which correlates were significantly associated with CRP; the partial R² value was computed to assess the contribution of each significant correlate to CRP variability. We also assessed the fold change of CRP for each predictor. Analyses were conducted with SAS version 9.2 (SAS Institute Inc., Cary, North Carolina). A 2-sided p value <0.05 was considered statistically significant.

In a subgroup analysis of 4,748 participants who had fasting insulin and fasting glucose information available, we analyzed the relation of obesity, insulin resistance, and diabetes to age- and gender-adjusted CRP concentration using general linear models (PROC GLM in SAS).

To analyze heritability, ASPEX, San Francisco, California, and RELTEST, Cleveland, Ohio, were used to check the consistency of the pedigrees. After resolution of all instances of nonpaternity and other errors in the family structures, the maximum likelihood heritability estimate for serum CRP concentration was obtained using a variance-components method.¹⁵

To analyze genetic linkage, the potential confounding influences of age, gender, and BMI on the distribution of CRP were removed by regression. Quantitative trait locus linkage analysis was performed using the multipoint variance components approach as implemented in MERLIN.¹⁶ A logarithm of odds score ≥3.3 was taken as evidence of significant linkage, and a logarithm of odds score ≥1.9 but <3.3 was taken as evidence of suggestive linkage.¹⁷ The Marshfield age- and gender-averaged maps were used in the linkage analyses.

To estimate the probability of obtaining false-positive evidence of linkage, we conducted gene-dropping simulations using Merlin. Marker data were simulated under the null hypothesis of no linkage or association to observed phenotypes while retaining the same pedigree structures, maps, marker allele frequencies, and missing data patterns. We simulated 2,000 replicates and conducted the same linkage analyses as described earlier. The probability of obtaining a false-positive result was defined as the proportion of replicates for which we obtained a specified logarithm of odds score or higher.

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Results 

In our large community-based cohort of African Americans, the mean CRP concentration was 5.1 ± 9.0 mg/L for the entire cohort and 1.8 ± 1.9 mg/L for the reference subsample. The characteristics of the study sample of 4,919 participants (mean age 55 ± 13 years, 63% women) are listed in Table 1. The mean age of the entire cohort of 5,302 was the same as that of the study sample (55 ± 13 years). There was only a 1 percentage point difference in the proportion of women in the entire cohort (64%) compared with that in the study sample. Subsequent results presented in this report are limited to the study sample of 4,919. A large percentage of the participants were obese (40.9% men, 60.0% women). Approximately 18% had diabetes. Also listed in Table 1 are the characteristics of participants in the reference subsample and the family cohort. As anticipated given the exclusion of subjects with major CVD risk factors and CVD, the reference sample participants were younger than the broad sample.

Table 1. Jackson Heart Study participant characteristics by study sample

Variable	Sample
	Broad		Reference		Family
	Men	Women	Men	Women	Men	Women
	(n = 1,810)	(n = 3,109)	(n = 408)	(n = 393)	(n = 457)	(n = 860)
Age (yrs)	54±13	55±13	47±13	48±12	49±15	50±14
Current cigarette smokers⁎	18.5%	10.1%			20.1%	10.7%
Systolic blood pressure (mm Hg)	128±18	127±19	116±10	112±12	126±17	124±19
Diastolic blood pressure (mm Hg)	81±11	77±10	77±8	73±8	81±10	78±10
Pulse pressure (mm Hg)	46±15	49±16	39±10	39±10	45±15	46±16
Hypertensive medication⁎	45.5%	57.1%			36.7%	49.0%
Hypertension⁎	59.8%	64.3%			50.6%	57.3%
BMI (kg/m2)	30±6	33±7	26±3	26±3	30±7	33±8
Obese (BMI ≥30 kg/m2)⁎	40.9%	60.0%			37.9%	63.8%
Waist (cm)	101±15	100±17	90±9	84±9	100±16	100±17
Fasting glucose (mg/dl)	102±38	102±38	89±7	86±8	100±40	98±36
Diabetes mellitus⁎	16.6%	19.2%			12.5	15.7%
Total cholesterol/high-density lipoprotein cholesterol	4.6±1.5	3.9±1.2	4.3±1.4	3.6±1.1	4.6±1.5	3.9±1.2
Lipid-lowering medication⁎	12.2%	12.6%			8.8%	10.4%
Hormone replacement therapy⁎	NA	21.6%			NA	20.1%
Prevalent CVD⁎	12.6%	8.9%			8.4%	7.1%

Data are expressed as meany ± SD or as percentages.

NA = not applicable.

Table 2 lists the distributions of CRP concentrations by gender and age in the broad study cohort (n = 4,919) and the reference sample (n = 801). For the broad sample and the reference sample, CRP concentrations were higher in women than in men.

Table 2. Distribution of C-reactive protein levels in participants in the Jackson Heart Study by age, gender, and sample

Variable	n	CRP (mg/L)
		Mean	SD	25th Percentile	Median	75th Percentile
Broad sample
Total	4,919	5.1	9.0	1.1	2.7	5.6
Men	1,810	3.6	9.8	0.8	1.7	3.7
Women	3,109	6.0	8.4	1.5	3.5	6.9
Age (yrs)
21–34	229	3.7	5.5	0.6	1.6	4.1
35–44	943	4.8	7.7	0.9	2.4	5.3
45–54	1,206	5.1	7.0	1.1	2.8	6.0
55–64	1,327	5.4	11.9	1.2	3.0	5.9
65–74	927	5.3	9.0	1.3	2.8	5.7
≥75	287	4.8	7.7	1.1	2.3	5.1
Reference sample
Total	801	1.8	1.9	0.5	1.0	2.5
Men	408	1.5	1.6	0.4	0.9	2.0
Women	393	2.1	2.1	0.5	1.2	2.8
Age (yrs)
21–34	93	1.2	1.4	0.3	0.7	1.7
35–44	279	1.7	1.7	0.4	1.0	2.3
45–54	208	2.0	2.2	0.5	1.0	2.8
55–64	139	2.1	2.0	0.6	1.4	2.7
65–74	60	1.9	1.8	0.8	1.3	2.6
≥75	22	2.3	2.2	0.7	1.4	3.6

In age- and gender-adjusted regressions, CRP concentration was significantly related to advancing age, female gender, higher blood pressure (systolic and pulse pressure), larger body size (BMI, waist circumference), glucose measures (diabetes, fasting glucose concentration), current cigarette smoking, higher lipid concentrations (total cholesterol/high-density lipoprotein ratio, triglycerides), medications (higher with hypertensive therapy and hormone replacement therapy, lower with lipid-lowering therapy), and prevalent CVD (Table 3).

Table 3. Age- and gender-adjusted correlates of log-transformed C-reactive protein

Variable	Fold Change in CRP (95% Confidence Interval)	p Value
Age per 10 yrs⁎	1.05(1.03–1.08)	0.0002
Women vs men†	1.81(1.69–1.94)	<0.0001
Systolic blood pressure per 20 mm Hg	1.07(1.03–1.11)	0.0004
Diastolic blood pressure per 10 mm Hg	1.00(0.97–1.03)	0.95
Pulse pressure per 10 mm Hg	1.06(1.03–1.08)	<0.0001
Waist circumference per 15 cm	1.50(1.46–1.54)	<0.0001
BMI per 5 kg/m2	1.40(1.37–1.43)	<0.0001
Current cigarette smoking, yes vs no	1.30(1.18–1.44)	<0.0001
Fasting glucose per 40 mg/dl	1.16(1.12–1.20)	<0.0001
Diabetes status, yes vs no	1.30(1.19–1.42)	<0.0001
Total cholesterol/high-density lipoprotein cholesterol ratio	1.11(1.08–1.14)	<0.0001
Triglycerides per 100 mg/dl	1.22(1.17–1.28)	<0.0001
Hypertension treatment, yes vs no	1.42(1.32–1.53)	<0.0001
Lipid-lowering therapy, yes vs no	0.78(0.71–0.86)	0.009
Hormone replacement therapy, yes vs no	1.50(1.35–1.66)	<0.0001
Prevalent cardiovascular disease, yes vs no	1.13(1.01–1.27)	0.03

In stepwise regression, the amount of variability in CRP explained by clinical covariates was 23.8% (Table 4). After forcing in age and gender, we found that increasing BMI, hormone replacement therapy, current smoking status, waist circumference, triglycerides, fasting glucose, and pulse pressure were positively related and lipid-lowering therapy and diastolic blood pressure were inversely related to CRP variability. BMI contributed 57% of the variability in CRP explained by standard clinical covariates (partial R² = 0.1360, p <0.0001).

Table 4. Clinical correlates of C-reactive protein concentrations: stepwise linear regression model (R² = 0.238)

Variable	Fold Change in CRP (95% Confidence Interval)	Partial R2⁎	p Value
Age per 10 yrs	1.05(1.02–1.08)	0.0027	0.0018
Women vs men	0.91(0.80–1.04)	0.0543	0.1833†
Body mass index per 5 kg/m2	1.27(1.22–1.32)	0.1360	<0.0001
Current hormone replacement therapy, yes vs no	1.61(1.47–1.77)	0.0153	<0.0001
Current cigarette smoking, yes vs no	1.43(1.31–1.57)	0.0107	<0.0001
Waist circumference per 15 cm	1.17(1.12–1.23)	0.0071	<0.0001
Triglycerides per 100 mg/dl	1.10(1.05–1.15)	0.0038	<0.0001
Lipid-lowering therapy, yes vs no	0.78(0.71–0.86)	0.0034	<0.0001
Fasting glucose per 40 mg/dl	1.06(1.02–1.10)	0.0021	0.0010
Diastolic blood pressure per 10 mm Hg	0.96(0.94–0.99)	0.0010	0.0113
Pulse pressure per 10 mm Hg	1.03(1.01–1.05)	0.0012	0.0061

Candidate covariates for selection included BMI, waist circumference, current cigarette smoking, total cholesterol/high-density lipoprotein cholesterol ratio, triglycerides, blood glucose, diabetes, systolic blood pressure, diastolic blood pressure, and pulse pressure, medications (antihypertensive, lipid lowering, aspirin, hormone replacement), and prevalent CVD.

Figure 1 shows the relation of age- and gender-adjusted CRP concentrations by obesity, diabetes, and insulin resistance status (in subjects without diabetes). Mean CRP concentrations were higher in participants with compared with those without obesity, regardless of insulin resistance or diabetes status. For obese and nonobese participants, the age- and gender-adjusted linear models suggested that mean CRP concentrations were significantly higher in individuals without diabetes but with insulin resistance compared with those without insulin resistance. There was no significant difference between subjects without diabetes with insulin resistance and participants with diabetes for obese or nonobese participants. There was no interaction between insulin resistance status, diabetes status, and obesity (p = 0.46).

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• Figure 1. 

  Age- and gender-adjusted relation of obesity, insulin resistance (IR; in participants without diabetes mellitus [DM]), and DM to CRP concentration. Log CRP concentrations were age and gender adjusted; back-transformed geometric means are displayed. SAS omits records with a single missing datum. Note that missing data may occur for different measures and not the same measure. ^*Assessed for a significant difference in CRP concentration between subjects with versus without obesity after adjusting for DM and IR. ^†Assessed for a significant difference in CRP concentrations adjusting for obesity between participants without DM who did not have IR (referent group) compared with participants without DM who had IR and participants with DM. There was no significant interaction between obesity, IR (in participants without DM), and DM. There were 171 missing data on IR status (“IR no” and “IR yes”) due to missing data on fasting insulin and/or fasting glucose. There was no significant difference between DM and “IR yes” for subjects who were not obese. Similar results were true for obese subjects. No difference was found between groups denoted by the same letter; differences were found between groups denoted by different letters.

The heritability for age-, gender-, and BMI-adjusted log CRP was 0.45 (SE 0.06, kurtosis −0.0172). Plots of the logarithm of odds scores on all 22 autosomes obtained from the initial multipoint variance-components linkage analyses for log CRP are presented in Figure 2. The peak logarithm of odds scores in this genome scan are listed in Table 5. The strongest evidence for linkage to CRP was observed on chromosome 11 (maximum logarithm of odds score 2.72, nominal p = 0.0002, empirical genomewide p = 0.065) near marker D11S1993, in the 11p13 to 11p11.2 region, 54 cM from p-ter.

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• Figure 2. 

  Multipoint logarithm of odds (LOD) scores by chromosome (CHR) for log-transformed CRP, adjusted for age, gender, and BMI.

Table 5. Adjusted logarithm of odds scores >1.0 for log-transformed C-reactive protein residual values obtained from multiple regression analysis

LOD = logarithm of odds.

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Discussion 

We report the distribution, reference ranges, correlates, heritability, and genetic linkage for CRP concentrations in the cohort, a large population-based study of African Americans with a high risk for CVD. Traditional CVD risk factors explained 24% of the variability in CRP concentrations, with BMI explaining 14% of the variability. Furthermore, we observed that CRP concentrations were moderately heritable (0.45) and have evidence for suggestive linkage to chromosome 11 (logarithm of odds score 2.72).

Similar to most cohorts, CRP concentrations were higher in women relative to men.¹⁸ Recent data suggest that CRP concentrations differ by race. In the racially mixed Dallas Heart Study cohort, CRP concentrations were higher in African Americans compared with whites (median 3.0 vs 2.3 mg/L, p <0.001). After adjustment for traditional cardiovascular risk factors, estrogen and statin use, and BMI, a CRP concentration >3 mg/L remained more common in white women (odds ratio 1.6, 95% confidence interval 1.1 to 2.5) and black women (odds ratio 1.7, 95% confidence interval 1.2 to 2.6) but not in black men (odds ratio 1.3, 95% confidence interval 0.8 to 1.9) compared with white men.¹⁹ Ethnic and racial variation in CRP concentrations was noted in the Third National Health and Nutrition Examination Survey (NHANES III), with the highest concentrations seen in non-Hispanic black men and Mexican American women.²⁰ In the Women's Health Study (WHS), CRP concentrations were notably higher in African American women.²¹

In the stepwise linear regression model, BMI, waist circumference, diastolic blood pressure, and fasting glucose significantly contributed to the variability of CRP, in addition to hormonal and lipid-lowering therapy. The relation of CRP to traditional cardiovascular risk factors observed in the cohort is similar to findings in other cohorts. In NHANES III, cigarette smoking, increased age, BMI, and systolic blood pressure in men and BMI and diabetes in women were strongly associated with CRP concentrations.¹⁸ In the Coronary Artery Risk Development in Young Adults (CARDIA) study, CRP was associated with hypertension in white and African American young adults, but in contrast to the finding in older cohorts such as ours, the association was no longer present after adjusting for BMI.²²

In our cohort, we found that subjects with diabetes and those without diabetes but with insulin resistance had higher CRP concentrations compared with those without insulin resistance or diabetes. There was no significant difference between CRP concentrations in individuals with diabetes and individuals without diabetes but with insulin resistance. Additionally, obesity was not an effect modifier on the relation between insulin resistance, diabetes, and CRP. Our data are consistent with those from several other studies.²³ For example, in the Risk Factors in Impaired Glucose Tolerance for Atherosclerosis and Diabetes (RIAD) study, those who were at risk for type 2 diabetes had higher CRP concentrations and were likely to be insulin resistant.²⁴

Several recent human studies have indicated significant genetic effects on variation in inflammatory markers.²⁵ Until now, however, there have been limited data on the heritability of CRP concentrations in African Americans. In the predominantly white National Heart, Lung, and Blood Institute Family Heart Study, investigators studied the familial aggregation of 3 systemic markers of inflammation, including CRP, and found evidence of substantial heritability (35% to 40%) for CRP concentrations.²⁶ In the Framingham Heart Study, investigators conducted variance-components linkage analyses of blood concentrations of 4 biomarkers of vascular inflammation; the heritability of CRP was estimated to be 28.2%, and the only adjusted logarithm of odds score >1.5 for CRP was located at chromosome 14q31.3.²⁷

The results of this study need to be confirmed by replication in multiple studies and ethnic cohorts. Our study was cross-sectional and observational. Hence, we cannot establish causal relations or the temporality of the observed association; we acknowledge that increased CRP concentration contributes to the development of risk factors, risk factors may precede and predispose to inflammation, the relations may be bidirectional, or the associations may be secondary to other factors that we did not model. In addition, the generalizability to other ethnicities and races or individuals of African ancestry in other states or countries is uncertain. Balanced against these caveats is the routine ascertainment of CRP concentrations and covariates in a large community-based cohort of African Americans.

Our study suggests that genetic and environmental risk factors, particularly obesity, contribute substantially to concentrations of CRP in African Americans. The high prevalence of obesity in our cohort and the important contribution of obesity to variability in CRP concentrations suggest that weight loss may be a critical strategy to attenuate the contribution of systemic inflammation in the development of cardiovascular risk factors and outcomes in this group. Given the disproportionate burden of CVD in the African American community, future investigations should focus on the relation of CRP to incident CVD to establish optimal threshold values for estimating risk in this group. In addition, the substantial heritability of CRP and recent data suggesting that CRP polymorphisms contribute to CVD risk underscore the importance of further research into genetic factors contributing to CRP variation in African Americans.²⁸

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Acknowledgment 

We thank the staff and participants in the Jackson Heart Study for their important contributions.

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