Author + information
- Received December 4, 2003
- Revision received February 10, 2004
- Accepted March 16, 2004
- Published online July 7, 2004.
- John F Keaney Jr, MD, FACC*,†,* (, )
- Joseph M Massaro, PhD§∥,
- Martin G Larson, ScD∥,
- Ramachandran S Vasan, MD, FACC*,‡∥,
- Peter W.F Wilson, MD, FACC*,∥,
- Izabella Lipinska, PhD†,
- Diane Corey, BS∥,
- Patrice Sutherland, BS∥,
- Joseph A Vita, MD, FACC*,† and
- Emelia J Benjamin, MD, ScM, FACC*,‡∥
- ↵*Reprint requests and correspondence:
Dr. John F. Keaney, Jr., Boston University School of Medicine, Whitaker Cardiovascular Institute, 715 Albany Street, Room W507, Boston, Massachusetts 02118, USA.
Objectives We sought to determine the clinical factors and heritability associated with inflammation measured as circulating levels of soluble-intercellular adhesion molecule-1 (sICAM-1) in a community-based cohort.
Background Several prospective studies indicate that circulating sICAM-1 is predictive of future cardiovascular events. However, in some studies this predictive value is lost after multivariable adjustment for traditional cardiovascular disease (CVD) risk factors. We addressed the heritability of sICAM-1 and its relation to CVD risk factors in a community-based cohort.
Methods We examined 3,295 subjects from the Framingham Heart Study and measured sICAM-1 levels. We then used linear and stepwise multivariable regression to determine predictors or sICAM-1 levels.
Results In age- and gender-adjusted regression models, increased sICAM-1 levels were positively associated with age, total/high-density lipoprotein cholesterol, systolic blood pressure, body mass index (BMI), blood glucose, diabetes, smoking, and prevalent CVD. In stepwise multivariable regression models, sICAM-1 levels remained associated with age, female gender, total/high-density lipoprotein cholesterol ratio, BMI, blood glucose, smoking, and prevalent CVD. The residual heritability of sICAM-1 was 24%.
Conclusions In addition to prevalent CVD, established CVD risk factors and non-traditional ones such as BMI were associated with systemic inflammation as determined by sICAM-1 levels. There also is significant heritability of sICAM-1, which suggests a genetic component to systemic inflammation.
The notion that inflammation plays a role in the development of clinical manifestations of atherosclerosis now is firmly established (1). The recruitment of inflammatory cells into the arterial wall is dependent upon cellular adhesion molecules and begins with leukocyte rolling on the endothelium that is facilitated by endothelial expression of P-selectin and its interaction with leukocyte P-selectin glycoprotein ligand-1 (2). Firm leukocyte adhesion requires an interaction between leukocyte beta1and beta2integrins and endothelial adhesion molecules such as vascular cell adhesion molecule-1 and intracellular adhesion molecule-1, respectively (3). With respect to the latter, several prospective studies have demonstrated that circulating soluble levels of intracellular adhesion molecule-1 (sICAM-1) are predictive of future cardiovascular events (4–6)and the development of peripheral arterial disease (7). The independent predictive value of sICAM-1 with respect to incident cardiovascular disease (CVD) is controversial because it is lost after multivariable adjustment for traditional cardiovascular risk factors in some studies (6)but not others (4,5,7). To address this issue, we examined the heritability and cross-sectional correlates of serum sICAM-1 levels in a community-based cohort.
The design and selection criteria of the Framingham Offspring study have been described elsewhere (8). The current sample was derived from the 3,539 participants attending the seventh examination cycle (1998 to 2001), and all procedures were approved by the Institutional Review Board of Boston Medical Center. Attendees underwent a routine physical examination, medical history, laboratory assessment of cardiovascular risk factors, and anthropometric measurements. The clinical definition of diabetes included fasting glucose ≥126 mg/dl, oral hypoglycemic use, or insulin use. Information about prior CVD events (coronary heart disease [CHD], stroke, intermittent claudication, congestive heart failure [CHF]) was obtained by medical histories, physical examinations at the Heart Study (every 4 years), and hospitalization and personal physician records. The latter were reviewed by a panel of three experienced investigators using previously described criteria (9). Subjects were excluded if they underwent physical examination off-site (n = 205), if serum was unavailable (n = 30), or if covariate data were missing (n = 9), which left 3,295 subjects for the current investigation.
Determination of sICAM-1
Serum samples were collected and stored at −70°C. For analysis, samples were thawed at room temperature, vortexed vigorously, and the sICAM-1 determined using a commercially available enzyme-linked immunosorbent assay (R & D Systems, Minneapolis, Minnesota) according to the manufacturer's instructions and expressed as ng/ml. Samples were analyzed in duplicate with an average intra-assay coefficient of variation of 3.7 ± 2.4%. All samples with a coefficient of variation greater than two standard deviations from this mean (8.8%) were repeated in duplicate, and the mean of the repeat duplicate values was used in this analysis.
Ninety-nine percent of the sICAM-1 values were within the range of 29 to 550 ng/ml, and the distribution was approximately normal in this range. Approximately 1% of sICAM-1 values were between 543 ng/ml and the maximum of 1,332 ng/ml. The distribution of sICAM-1 was asymmetric, but analyses performed on raw (untransformed) and log-transformed data were virtually identical. We present untransformed data because they are more easily understood clinically.
Age- and gender-adjusted linear regression models were constructed to assess relations of sICAM-1 to the following individual variables: total/high-density lipoprotein (HDL) cholesterol, systolic blood pressure (BP), diastolic BP, body mass index (BMI), waist-to-hip ratio, fasting glucose level, history of diabetes, smoking, hypertension treatment, and history of myocardial infarction (MI), CHF, or CVD. Gender and age interactions also were tested for each variable listed above. Stepwise linear regression multivariable models (10)were constructed with sICAM-1 against the above variables with a p < 0.10 threshold for inclusion. The Framingham CHD Risk Score was calculated as described previously (11)except age was not included, because we age-adjusted sICAM-1 levels in analyses using the risk score. In addition, adjusted logistic regression models were constructed with prevalent CVD as the outcome to assess its relation with sICAM-1 (12). Analyses were run using SAS version 8.1 (Cary, North Carolina) (13). Any two-sided p value less than 0.05 was considered to be statistically significant.
We used Sequential Oligogenic Linkage Analysis Routines (14)to estimate residual heritability of sICAM-1, that is, the proportion of variability attributable to genetic effects after accounting for measured covariates. The underlying model assumed that trait variation could be partitioned into genetic and environmental (measured covariate) factors. The genetic component was assumed to be polygenic without dominance components. We estimated residual heritability after accounting for gender and age and then after accounting for multiple additional covariates. The portion of variation resulting from measured covariates was determined using a regression model with men and women combined.
Subject characteristics and individual predictors of sICAM-1
Characteristics of the study sample are displayed in Table 1. As expected, CVD was more prevalent in men (18%) than women (9%). Because men and women exhibited similar serum levels of sICAM-1 and because each covariate effect on sICAM-1 was similar for men and women, gender-pooled analyses were performed. Age- and gender-adjusted regression was conducted using variables from Table 1as correlates of sICAM-1 (Table 2). Advancing age positively correlated with sICAM-1, as was total/HDL cholesterol ratio, systolic BP, diabetes, history of hypertension treatment, smoking, MI, and CVD. Serum glucose also was positively associated with sICAM-1. Obesity, measured as overall adiposity (BMI) or its pattern (waist-to-hip ratio), also emerged as a strong positive correlate of sICAM-1, but we found no significant associations between sICAM-1 and either heart failure (p = 0.20) or diastolic BP (p = 0.66).
Multivariable correlates of sICAM-1 levels
The results of age- and gender-adjusted stepwise multivariable linear regression models are shown in Table 3. Age remained a highly significant correlate of sICAM-1, and gender emerged as a significant correlate in the multivariable model, with women averaging sICAM-1 levels that were 9 ng/ml higher than men. The emergence of gender as a predictor of sICAM-1 was driven by the entrance of total/HDL cholesterol ratio in the model because women had higher average sICAM-1 levels than men at any given level of total/HDL cholesterol ratio. Other strong positive predictors of sICAM-1 were smoking and total/HDL cholesterol ratio. Smokers demonstrated an adjusted mean sICAM-1 that was 25% higher than non-smokers (309 ± 100 ng/ml vs. 251 ± 78 ng/ml, respectively). Fasting glucose also was associated with increased sICAM-1 levels because each 25-mg/dl increase in fasting glucose was associated with a 6-ng/ml adjusted mean increase in sICAM-1. Although some previous studies have suggested that sICAM-1 is merely a reflection of CVD risk factors, we found that prevalent CVD was highly associated with sICAM-1 levels (Table 3) and that this relation was not related to time from CVD diagnosis (p = 0.70 for time effect).
To examine the relation between established CHD risk and sICAM-1, we plotted age-adjusted mean sICAM-1 (± one standard error) by gender-specific Framingham CHD risk score (11)quintile for men and women without prevalent CVD (Fig. 1). We found that increasing quintiles of risk scores were associated with increasing levels of sICAM-1. To determine whether sICAM-1 adds significantly to the risk factor profile of CVD beyond traditional risk factors, we performed multivariable logistic regression with prevalent CVD as the outcome variable and found that circulating sICAM-1 levels remained a significant risk factor (p = 0.002) even after adjusting for the components of the Framingham risk score. In fact, after adjusting for all variables in Table 1(except history of MI and CHF), sICAM-1 remained a significant risk factor for prevalent CVD (OR 1.10 for a 50-ng/ml increase in sICAM-1, 95% confidence interval of 1.03 to 1.17; p = 0.004).
In addition to these variables, our data support a relation between obesity and sICAM-1. With respect to BMI, we found that each 5 kg/m2increase was associated with a 5-ng/ml increase in sICAM-1 levels (p = 0.0002 after adjustment for variables in the stepwise model). To ensure this relation was truly a reflection of obesity, we substituted waist-to-hip ratio for BMI in the multivariable model and we found it also was significantly associated with serum sICAM-1 levels (p = 0.004). To characterize the relation between obesity and this marker of inflammation, we plotted mean sICAM-1 as a function of normal, overweight, and obese BMI levels in non-smokers and we observed a progressive relation between increasing BMI category and sICAM-1 levels (Fig. 2).
With regard to the variability in sICAM-1 levels, the final multivariable model explained approximately 10.2% of the variability (Table 3). Among variables in Table 1, smoking was the most important predictor of sICAM-1 levels and alone accounted for 6% of the variability (Table 3). The heritability of sICAM-1 was estimated as 25.7 ± 5.9% (estimate ± standard error) adjusted for gender and age and as 24.3 ± 6% after adjustment for multiple covariates (p < 0.0001). Taking into account correlations among siblings in the multivariable model had no material impact on the analyses listed in Table 3.
We performed several secondary analyses to ensure that our results were not confounded by the presence of CVD or medications. We found that excluding patients with CVD had no material effect on the results contained in Table 3. Similarly, excluding patients on hypertension treatment or on lipid-lowering medication had no material impact on the results.
Considerable evidence now links both atherosclerosis and coronary artery disease events to a state of vascular inflammation (15). Consistent with this notion, we found that elevated levels of sICAM-1 were related to CVD risk factors and prevalent CVD. We also found that sICAM-1 was related to CVD risk factors after excluding subjects with prevalent CVD, suggesting sICAM-1 is linked to early atherosclerosis. The notion that sICAM-1 may reflect preclinical early atherosclerosis is not without precedent. Ligands for ICAM-1 include the beta2integrins CD11a/CD18 (LFA-1) and CD11b/CD18 (Mac-1), which are present on inflammatory cells such as neutrophils, monocytes, and lymphocytes. Atherosclerotic lesions of all stages demonstrate expression of ICAM-1 (16), and mice deficient in either CD18 or ICAM-1 are resistant to diet-induced atherosclerosis (17). Moreover, in vivo studies in apolipoprotein E-deficient mice (18)and humans (19,20)suggest that sICAM-1 levels parallel the extent of atherosclerosis. Therefore, available data indicate that the development of atherosclerosis is, in part, dependent upon ICAM-1.
In addition to the morphologic development of atherosclerosis, clinical studies suggest a relation between ICAM-1 and CVD events. For example, prospective case-control studies have linked elevated sICAM-1 levels to incident CHD (4–6,21)and peripheral vascular disease (7). With respect to the former, this relationship was lost after multivariable adjustment for traditional cardiovascular risk factors in some studies (6,21), suggesting that sICAM-1 levels are simply a “barometer” for established risk factors. Indeed, Rohde et al. (22)determined sICAM-1 levels in 948 participants of the Physician's Health Study and found significant independent associations with smoking, diabetes, systolic BP, and a positive family history of coronary disease. With respect to CVD risk factors, our data agree with that of Rohde et al. in that age, smoking, and diabetes were all positively associated with sICAM-1 levels (Table 3). In contrast, this study does not support the notion that sICAM-1 is simply a reflection of CVD risk factors because we did find an association between prevalent CVD and sICAM-1 levels that was independent of traditional CVD risk factors and the Framingham Risk Score.
The data presented here demonstrate an association between indices of obesity and sICAM-1 levels, after adjusting for other CVD risk factors, which is consistent with a connection between obesity and inflammation. Indeed, several studies have found that C-reactive protein, a systemic marker of inflammation, is positively associated with BMI (23–25). Smaller studies have suggested that adhesion molecules (26)are associated with obesity and improve with weight loss (27). Although the precise mechanism whereby obesity is linked to inflammation remains unclear, adipose tissue is now recognized as a source of proinflammatory cytokines such as tumor necrosis factor-alpha (28)and interleukin-6 (29). Given that circulating levels of C-reactive protein are readily elevated in response to interleukin-6 (30,31), it is plausible that adipose secretion of inflammatory cytokines could lead to increased circulating levels of C-reactive protein. A similar phenomenon may explain the relation of adiposity to sICAM-1 because human endothelial cells in culture release ICAM-1 in response to cytokines such as tumor necrosis factor-alpha and interleukin-1 (32).
It is intriguing that both obesity and prevalent CVD are associated with inflammation, because the link between obesity and CVD has been contentious. Past studies found that the independent effect of obesity on CVD was modest, leading to conclusions that it was of limited significance (33–35). More recent investigation indicates that obesity has a profound impact on other CVD risk factors and, thus, should be considered an independent hazard for CVD. For example, clusters of more than two CVD risk factors are more common in obese subjects (BMI >30) than in subjects not overweight or obese (BMI <25) (36), and weight reduction is associated with a concomitant reduction in global risk factor sum (37). In light of the data presented here on sICAM-1 and obesity, it is attractive to speculate one component of any link between obesity and other CVD risk factors is the promotion of systemic inflammation. Although the contribution of obesity to sICAM-1 was modest, such speculation fits well with emerging evidence that inflammation may be a cause, rather than a consequence, of active atherosclerosis. Indeed, the injection of a periodontal pathogen in apolipoprotein E-heterozygous mice enhances the development of atherosclerosis (38)and the inflammatory marker C-reactive protein itself induces endothelial cell activation (39)and endothelial dysfunction (40). Taken together, these data support speculation that obesity may partially contribute to the clinical manifestations of atherosclerosis through the promotion of a heightened inflammatory state.
To our knowledge, this is the first report of the heritability of sICAM-1, which we found to be 24%. This level of heritability is comparable with the heritability of left ventricular mass (41). There is increasing interest in the relationship between genetic variation in inflammatory markers and the risk of clinical and subclinical CVD (42). Polymorphisms in sICAM-1 have been related to diabetes (43), CHD, and MI (44). However, the genetic basis of vascular inflammation and the relation between genetic polymorphisms in inflammatory genes and CVD are incompletely understood. Our finding that vascular inflammation is modestly heritable would suggest that its genetic basis merits further investigation.
There are several limitations of the present study that warrant consideration. First and foremost, we used sICAM-1 as an index of inflammation. Although plasma levels of soluble adhesion molecules are thought to originate from vascular cells through proteolytic cleavage and shedding (32), the precise source of sICAM-1 and factors that influence its clearance from plasma remain unknown. Therefore, our results could merely represent some change in the clearance of sICAM-1 rather than a reflection of its production per se. Additionally, because the sample was derived from a single measurement in ambulatory volunteers, sICAM-1 levels may have been confounded by medication status. We investigated such potential confounding by separately analyzing people not receiving lipid-lowering or hypertension medications and noted consistency in findings with those observed in the entire sample. Finally, the Framingham cohort is not ethnically diverse, and the extent to which our findings are applicable to other ethnic groups is not known at this time.
In summary, the data presented here support an association between circulating sICAM-1 levels and prevalent CVD as well as with established CVD risk factors such as age, smoking, increasing glucose levels, and total/HDL cholesterol ratio. Circulating levels of sICAM-1 were also modestly related to obesity, suggesting one mechanism whereby obesity may contribute to the clinical manifestations of CVD. Finally, we found modest heritability of sICAM-1 levels, suggesting that investigation into the genetic determinants of inflammation is likely to be fruitful.
We thank Josee Dupuis for the Sequential Oligogenic Linkage Analysis Routines analysis.
☆ Supported by NIH/NHLBI contract N01-HC-25195 and N01-HV-28178 and NIH grants HL64753 (E.J.B.), DK55656 (J.F.K.), HL70139 (R.S.V.), and HL60886 (J.A.V. and J.F.K). Dr. Keaney is an Established Investigator of the American Heart Association, and Dr. Vasan is the recipient of a research career award (HL04334) from the NIH.
- body mass index
- blood pressure
- coronary heart disease
- congestive heart failure
- cardiovascular disease
- myocardial infarction
- soluble intracellular adhesion molecule-1
- Received December 4, 2003.
- Revision received February 10, 2004.
- Accepted March 16, 2004.
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