analysis. Four Cox-proportional hazard models containing progres- sive levels of covariate adjustment were used to assess risk of inci- dent events associated with baseline sCD14 levels. The first model was minimally adjusted for demographic characteristics (age, sex, and race). The second model was additionally adjusted for traditional CVD risk factors (hypertension, systolic blood pressure, diabetes mellitus, smoking, low-density lipoprotein cholesterol). For analysis of mortality, the second model also included cystatin C, and baseline peripheral artery disease, stroke, coronary heart disease (CHD). The third model included additional adjustment for subclinical vascular disease as assessed by ABI and internal carotid wall thickness. The fourth model additionally included adjustment for plasma levels of other inflammation biomarkers, CRP, IL-6, and fibrinogen. Hazard ratios and 95% CI (hazard ratios, 95% CI) for biomarkers were com- pared qualitatively with those of other inflammation biomarkers.

Assessment of Association Between CD14 Genotype and CVD in Women’s Health Initiative

To assess the association between CD14 SNP genotype and CVD, we used data from a larger nested case–control sample of incident CHD and stroke from the Women’s Health Initiative.20 The sample included 3042 myocardial infarction (MI) and 2222 stroke EA cases and 296 MI and 251 stroke black cases. There were 2943 EA and 295 black controls without CHD or stroke. Genotyping and quality con- trol of CD14 SNPs was performed using the ITMAT/Broad/CARe (IBC) array at TGen (Phoenix, Arizona). Logistic regression models were adjusted for traditional risk factors (age, BMI, smoking, diabe- tes mellitus, hypertension, cholesterol) and principal components to control for population stratification.

Methods

CHS Cohort

The CHS is a prospective population-based cohort study of older adult men and women recruited from 4 US field centers: Forsyth County, NC; Sacramento County, CA; Washington County, MD; and Pittsburgh, PA. A total of 5201 participants (original cohort) were recruited in 1988–1989.16 An additional 687 primarily black par- ticipants were recruited in 1992–1993 (minority cohort) for a total cohort of 5888. The CHS baseline evaluation included demographic, lifestyle and medical histories, physical examination, fasting blood collection, and assessment of subclinical vascular disease by carotid ultrasound and ankle-brachial index (ABI).17 Informed consent was obtained using methods approved by institutional review committees at each study site. Genomewide genotyping was performed on 2952 EA and 528 black unrelated CHS participants with sCD14 measure- ments using the Illumina 370CNV platform. Details of the methods for measurement of plasma biomarkers, genotyping, fine-mapping, ascertainment of clinical CVD events during follow-up adjudication are described in the online-only Data Supplement.

Results

Relationship of sCD14 With Baseline CVD Risk Factors and Other Inflammation Biomarkers

CHS participant characteristics are summarized in Table I in the online-only Data Supplement, by race. sCD14 levels were approximately normally distributed with a mean±SD of 1641±348 (range 284–4030) ng/mL. sCD14 levels increased with age and differed significantly by sex (P<0.001) and by race (P<0.001). The mean values in EA women, EA men, black women, and black men were 1714±354, 1596±329, 1551±410, and 1454±392 ng/mL, respectively (Figure). The Spearman

Statistical Analysis

(body mass index [BMI], lipid levels, fasting glucose, insulin, CRP, IL-6, ABI, and carotid intima media thickness), or binary traits (diabetes mellitus, hypertension) were assessed using multiple lin- ear regression or logistic regression, respectively. Hypertension is defined as systolic blood pressure>140, diastolic blood pressure>90, or current use of antihypertensive medication. CRP and IL-6 were log-transformed to reduce skewness. To test for genetic associations with sCD14, linear regression was performed, assuming an additive genetic model, using PLINK18 for the genotyped data and Mach2qtl for the imputed data, adjusting for covariates of age, sex, and the first 10 eigenvectors derived from principal components analysis. For blacks, sCD14 was analyzed using log-transformed values in the genetic association analyses to assess statistical significance; means and standard errors were reported from the corresponding untrans- formed model for comparisons with EAs. Haplotype frequency esti- mation and association analyses were performed using the haplo.stats package for R.19 Estimation of sCD14 phenotypic variance explained by genomewide single-nucleotide polymorphisms (SNPs) was per- formed using the Genome-wide Complex Trait Analysis method, as described in the online-only Data Supplement.

BLACK WOMEN BLACK MEN WHITE WOMEN WHITE MEN )Lm/gn(( 41DCs 000,4000,3000,2000,10

We performed Cox proportional hazards models to test for associa- tion between sCD14 (or other inflammation biomarkers) and risk of incident CVD events or mortality. sCD14 and other biomarkers were analyzed continuously to estimate the effects of a 1-SD difference in value, as well as categorically using quintiles. The first quintile represented the reference group. For the continuous analysis, IL-6 and CRP were log transformed. Persons with adjudicated baseline prevalent disease relevant for each outcome were excluded before

Figure. Distribution of soluble CD14 according to ethnicity and sex. Median and interquartile ranges are indicated by the middle band and box edges, respectively. The whiskers indicate upper and lower adjacent values. Dots indicate values outlying 1.5 times the interquartile range (IQR) above the 75th percentile and 1.5 times the IQR below the 25th percentile.

Figure. Distribution of soluble CD14 according to ethnicity and sex. Median and interquartile ranges are indicated by the band and box edges, respectively. The whiskers indicate upper