Abstract
BACKGROUND:
Studies have shown that rheumatoid arthritis (RA) patients are two to five times more likely to develop premature cardiovascular disease, thus shortening their life expectancy by five to 10 years. This risk has risen to approximately 12.6% in the urban population and 7.4% in the rural population of India. The Framingham risk score (FRS) identifies patients at increased cardiovascular risk and helps determine the need for preventive interventions. An investigation of the patients’ coronary arteries and coronary artery calcification (CAC) – a measure of atherosclerotic plaque – has been found to be a strong predictor of cardiovascular disease.
OBJECTIVE:
To identify important biological markers for easy and non-invasive identification of cardiovascular disease in RA patients, and to investigate whether there is a relationship between the FRS and coronary artery atherosclerosis in RA patients.
METHODS:
The present study included 43 established RA patients and 50 healthy individuals (controls). Traditional and nontraditional risk factors were studied and compared with the control group. Insulin resistance was assessed using the homeostasis model of assessment of insulin resistance (HOMA-IR) and the homeostasis model of assessment of beta cell function. The FRS and the 10-year cardiovascular risk were compared between RA patients and controls. The presence of CAC was determined using electron-beam computed tomography, and the association between the FRS and CAC was examined.
RESULTS:
Significant differences in body mass index, waist circumference, rheumatoid factors (immunoglobulin [Ig]G, IgM and IgA) and inflammatory markers – C-reactive protein and erythrocyte sedimentation rate – were noted. There was significant correlation between HOMA-IR and body mass index, hypertension and C-reactive protein, but no correlation was seen with the homeostasis model of assessment of beta cell function. Significant differences were observed in the nontraditional biomarkers in RA patients, thus supporting their importance. Calcium deposition was observed in only seven RA patients.
CONCLUSIONS:
RA patients with increased C-reactive protein levels and erythrocyte sedimentation rates showed an increase in serum insulin levels and significant differences in HOMA-IR, thus indicating insulin resistance, which could lead to underlying progression of artherosclerosis. Significant differences were observed in the nontraditional risk factors, which could be chosen as biomarkers for endothelial dysfunction. There was a significant correlation between calcium score and the FRS in seven patients, suggestive of an underlying risk of atherosclerosis.
Keywords: Atherosclerosis, ELISA, HOMA-B, HOMA-IR, Inflammation, Insulin resistance, Rheumatoid arthritis
Rheumatoid arthritis (RA), a systemic inflammatory disorder that affects joints, has been reported in approximately 1% of the general population. Several studies have documented the increased mortality and morbidity rates in these patients (1,2), which could be due to underlying accelerated coronary artery and cerebrovascular atherosclerosis (observed in a majority of the cases). Women with RA are at twice the risk of developing myocardial infarction compared with women who do not have RA; however, this increased risk is also seen in men (3,4). Inflammation-mediated vascular endothelial dysfunction has been shown to lead to atherosclerosis, and has been found to be the major contributing factor to increased cardiovascular morbidity and mortality rates (5). Connective tissue and smooth muscle also correspond to sites of lipid deposition and plaque formation (6). Several reports on increased subclinical atherosclerosis in systemic lupus erythematosus and RA have been published; however, no such data are yet available in India. The prevalence of coronary artery disease (CAD) in India is nearly 10 times higher than that seen 40 years ago (7). The Framingham risk score (FRS) is an extensively studied index that predicts cardiovascular risk in the general population. It includes age, sex, smoking, blood pressure and cholesterol concentrations, and estimates the risk of coronary events by stratifying individuals into three risk categories: low (<10% risk of an event in 10 years), intermediate (10% to 20%) and high (>20%) Although the FRS is widely used in the general population to determine prognosis and the need for intervention, the value of this risk score is less clear in younger patients, women and patients with inflammatory diseases. In contrast to the general population, there is no information regarding the relationship between the cardiovascular FRS and coronary calcification in patients with RA. Therefore, we hypothesized that the cardiovascular FRS is associated with coronary calcification in patients with RA.
Published data show that in RA, both traditional and nontraditional risk factors contribute to the pathogenesis of cardiovascular disease (CVD) (8). Insulin resistance has been associated with inflammation in diabetes patients (9), which contributes to the metabolic syndrome, which includes dyslipidemia and impaired glucose metabolism (10). It has been shown that insulin resistance is a major contributor to CVD through the metabolic syndrome (11). However, there are also studies showing a 10% to 20% prevalence of diabetes in RA patients; the current literature also shows that diabetes predicts the increased rates of CVD (12). Hence, it would be interesting to investigate whether insulin resistance is also a contributory risk factor adding to the increased prevalence of cardiovascular mortality in RA patients.
METHODS
Patients
Forty-three established RA patients were studied and were diagnosed according to the American College of Rheumatology criteria. Most of the patients were older than 40 years of age and experienced cardiac problems. Patients were evaluated using the standardized clinical interview. The present study was approved by the institutional review committee for ethical issues, and the project was sanctioned by the Scientific Advisory Committee of the Medical Research Society.
The patients’ clinical histories were noted in the patient proforma, details regarding smoking habits were documented, and heights and weights were measured. Body mass index (BMI) in kg/m2 was calculated for each patient and control to identify the health status of the individual. Blood pressure was recorded, and blood was collected after a 12 h overnight fast for all routine laboratory investigations. Routine biochemical estimations were performed using commercially available kits (Randox Laboratories, USA). Blood samples were stored at −80°C until the specified kit for the tests were available.
In addition, for inflammatory markers, such as C-reactive protein (CRP) (ACTIVE Us-C Reactive Protein ELISA kit, Diagnostics Systems Laboratories Inc, USA) and erythrocyte sedimentation rate (ESR), special tests (ELISA and the Westerngren method) were performed in the hospital’s clinical laboratory. Insulin levels were estimated using ELISA kits from LINCO Research Inc, USA.
In RA patients, the rheumatoid factor (RF) isotypes (immunoglobulin [Ig]G, IgM and IgA) were determined using ELISA kits from INOVA Diagnostics Inc, USA. Disease activity was measured using the disease activity score of 28 joints (DAS 28). Recently, DAS 28 with CRP has been used as the score for disease management.
Insulin resistance was calculated using the homeostasis model of assessment of insulin resistance (HOMA-IR) and the homeostasis model of assessment of beta-cell function (HOMA-B) by using the following equations:
using HOMA of fasting glucose (mmol/L) and fasting insulin (mU/L) (13).
The FRS
The composite, simplified coronary prediction model built on the blood pressure and cholesterol categories proposed by the Joint National Committee on Blood Pressure and the National Cholesterol Education Program was used. This model includes age, total and high-density lipoprotein cholesterol, blood pressure and smoking, and was designed after a community-based cohort (the Framingham study) of more than 5000 people who were followed for 12 years (14).
Patients underwent a computed tomography scan of the chest to detect calcification of the arteries, which served as a surrogate measure of subclinical atherosclerosis.
Coronary artery calcification
All subjects underwent imaging with a Somatom (Siemens, Germany) – a 64 slice imaging system. Briefly, imaging was performed with a 100 ms scanning time and a single slice thickness of 3 mm. Sixty-four slices were obtained during a single-breath holding period, beginning at the aortic arch and proceeding to the level of the diaphragm. All the scans were read by a single expert investigator who was blinded to the subjects’ clinical status.
Exclusion criteria
Patients younger than 40 years of age and nonsmokers were excluded, as well as those with a history of diabetes. No other infections were noted.
Controls included 50 age-matched, healthy individuals without any history of illness or infections in the previous few months.
All parameters previously studied in the patients were also studied in the controls, and the results were compared, and statistical significance was determined.
The research was approved by the scientific advisory committee, and written consent was obtained from the patients before collecting blood samples and performing computed tomography scans.
Statistical analysis
The Mann Whitney U test was used for evaluation of statistical significance using SPSS version 16 (IBM Corporation, USA). Mixed-regression models for HOMA-IR and HOMA-B were used for correlation analysis. The correlation between the FRS and continuous clinical characteristics was performed using the Spearman’s correlation coefficient, ρ.
RESULTS
Clinical characteristics of patients with RA, and the traditional risk factors
The demographics of the 43 RA patients and the 50 healthy controls are presented in Table 1A. The average age of the RA patients was 51.84±8.90 years, which was slightly older than the controls. Seventy-six per cent of the RA patients were female, with a statistically significant BMI. Approximately 30% of the 43 patients had a BMI >30. Waist circumference and systolic blood pressure were found to be highly significant (P<0.001). These traditional risk factors, although highly significant, did not suggest CVD risk, thus necessitating specialized tests.
TABLE 1.
Patient demographics, clinical findings and laboratory analysis of traditional and nontraditional risk factors in rheumatoid arthritis (RA) patients compared with healthy controls
|
A: Traditional risk factors analyzed using the Mann-Whitney U test
| |||
|---|---|---|---|
| Demographic | RA patients (n=43) | Controls (n=50) | P |
| Age, years | 51.84±8.90 | 47±1.31 | <0.05 |
| Females, n (%) | 33 (76) | 30 (60) | – |
| Body mass index, kg/m2 | 24.77±0.7 | 22.69±0.30 | <0.01 |
| Waist circumference, cm | 87.38±2.05 | 79.36±1.63 | <0.001 |
| SBP, mmHg | 133.25±2.60 | 117.12±1.38 | <0.001 |
| DBP, mmHg | 81.16±1.6 | 76.78±1.07 | <0.01 |
| Total cholesterol, mmol/L | 168.07±4.49 | 184.37±5.69 | <0.05 |
| HDL cholesterol, mmol/L | 49.18±2.19 | 45.62±1.59 | 0.30 |
| Triglycerides, mmol/L | 0.98± 0.06 | 1.06±0.06 | 0.38 |
Data presented as mean ± SE unless otherwise indicated. DBP Diastolic blood pressure; HDL High-density lipoprotein; SBP Systolic blood pressure
Nontraditional risk factors
Table 1B lists the important nontraditional risk factors studied that could be used as biomarkers for differentiating RA patients who are at a high risk for CVD. The levels of anticardiolipin antibodies (IgG and IgM), uric acid, osteoprotegerin and complement C3 were all highly significant when compared with controls.
B:
Nontraditional risk factors analyzed using the Mann-Whitney U test
| Variable | RA patients (n=43) | Controls (n=50) | P |
|---|---|---|---|
| Anticardiolipin M, MPL units/mL | 8.41±1.58 | 4.24±0.28 | <0.001 |
| Anticardiolipin G, GPL units/mL | 18.84±1.10 | 12.19±0.96 | <0.001 |
| Ox-LDL, mU/mL | 841.97±92.31 | 1008.8±109.97 | 0.43 |
| Uric acid, μmol/L | 589.47±48.08 | 965.75±590.2 | <0.001 |
| OPG, pg/mL | 342.62±59.77 | 86.48±7.13 | <0.001 |
| C1q CIC, μg/mL | 2.67±0.45 | 2.41±0.35 | 0.11 |
| Complement C3, g/L | 27.43±2.37 | 18.72±1.49 | <0.05 |
Data presented as mean ± SE. CIC Circulating immune complexes; OPG Osteoprotegerin; Ox-LDL Oxidized low-density lipoprotein
Comparison of diagnostic parameters of RA with controls
All parameters used to diagnose RA, such as RF isotypes (IgG, IgM and IgA), DAS28, the health assessment questionnaire for RA and the inflammatory markers, such as CRP and ESR, were found to be significant (Table 2; P<0.001).
TABLE 2.
Comparison of diagnostic parameters of patients with rheumatoid arthritis (RA) and healthy controls
| Variable | RA patients (n=43) | Controls (n=50) | P |
|---|---|---|---|
| Disease duration, months | 63±12 | NA | – |
| Rheumatoid factors | |||
| IgA, U | 96.716±37.09 | 4.05±0.64 | <0.01 |
| IgM, U | 115.47±20.77 | 7.5±3.07 | <0.001 |
| IgG, U | 70.89±28.87 | 5.65±3.80 | <0.05 |
| DAS28 | 5.93±1.12 | 0 | <0.001 |
| HAQ | 1.22±0.56 | 0.14±0.22 | <0.001 |
| ESR, mm | 65.1±34.16 | 32.44±22.93 | 0.001 |
| CRP, ng/dL | 0.069±0.020 | 0.029±0.0057 | 0.086 |
Data presented as mean ± SE. CRP C-reactive protein; DAS28 Disease activity score of 28 joints; ESR Erythrocyte sedimentation rate; HAQ Health assessment questionnaire; Ig Immunoglobulin; NA Not available
Insulin resistance using HOMA-IR
Insulin resistance was quantified in RA patients and controls by using HOMA-IR (Table 3). Significant levels of insulin were observed in patient serum, which corresponded to a significant difference in the HOMA-IR, indicating insulin resistance. Differences in HOMA-B were not significant and, thus, diabetes was not noted for these patients; however, an underlying cause for subclinical atherosclerosis was indicated.
TABLE 3.
Insulin resistance quantified by the homeostasis model of assessment of insulin resistance (HOMA-IR)
| Other risk factors | RA patients (n=43) | Controls (n=50) | P |
|---|---|---|---|
| Fasting glucose, mmol/L | 5.06±0.78 | 5.05±0.52 | 0.727 |
| Serum insulin, pmol/L | 53.44±5.15 | 35.09±3.23 | <0.001 |
| HOMA-IR | 1.72±0.97 | 1.12±0.7 | <0.001 |
RA Rheumatoid arthritis
Biomarkers of endothelial dysfunction
Table 4 lists the biomarkers of endothelial dysfunction. These include asymmetric dimethylarginine, total nitrate (combination of nitrate and nitrite levels), copper and zinc superoxide dismutase, angiotensin II and homocysteine levels. The nitrate, copper and zinc superoxide dismutase, angiotensin II and homocycteine levels were found to be highly significant. All of these markers are contributors to the increased prevalence of CVD seen in RA patients and, thus, can be used to identify RA patients at an early age.
TABLE 4.
Study of biomarkers of endothelial dysfunction in patients with rheumatoid arthritis (RA) compared with healthy controls, analyzed using the Mann-Whitney U test
| Variable | RA patients (n=43) | Controls (n=50) | P |
|---|---|---|---|
| ADMA, μmol/L | 0.96±0.049 | 0.86±0.04 | 0.04 |
| Total nitrate, μmol/L | 158.02±7.02 | 148.62±6.04 | 0.28 |
| Nitrite | 100.02± 4.64 | 120.40±6.71 | 0.04 |
| Nitrate | 58.00±6.77 | 28.22±3.72 | <0.001 |
| Cu/Zn SOD, ng/mL | 144.26±17.91 | 57.14±6.90 | <0.001 |
| Angiotensin II, pmol/L | 7729.44±517.08 | 3562.91±304.22 | <0.001 |
| Homocysteine, μmol/L | 19.41±1.22 | 14.27±1.24 | <0.01 |
Data presented as mean ± SE. ADMA Asymmetric dimethylarginine; Cu/Zn SOD Copper and zinc superoxide dismutase
The FRS for cardiovascular events
The composite, simplified coronary prediction model built on the blood pressure and cholesterol categories was designed after a community-based cohort (the Framingham study). Table 5 presents the data of RA patients and controls on the basis of these parameters, from which the FRS was calculated. The 10-year risk of cardiovascular events in females was 1.56% in RA patients compared with 0.85% of females in the control group. However, when the male score was calculated, it was not found to be significant. HOMA-IR was also found to be highly significant.
TABLE 5.
Components of the Framingham risk score for CV events
| RA patients (n=43) | Controls (n=50) | P | |
|---|---|---|---|
| Mean total cholesterol, mmol/L (range) | 168.97±29.18 (115) | 181.30±40.17 (181.3) | 0.17 |
| Smoking, % | 9.3 | 10 | |
| HDL, mmol/L | 49.5±14.4 | 45.44±11.13 | 0.472 |
| Systolic blood pressure, mmHg | 133.25±17 | 117.12±9.77 | <0.001 |
| Fasting glucose, mmol/L | 5.06±0.76 | 5.05±0.52 | 0.727 |
| Serum insulin, pmol/L | 53.44±5.15 | 35.09±3.23 | <0.001 |
| HOMA-IR | 1.72±0.97 | 1.12±0.7 | <0.001 |
| 10-year risk of CV events, % | 1.56 (Females) | 0.85 (Females) | <0.001 |
| 6 (Males) | 4.97 (Males) | 0.67 |
Data presented as mean ± SE unless otherwise indicated. CV Cardiovascular; HDL High-density lipoprotein; HOMA-IR Homeostasis model of assessment of insulin resistance; RA Rheumatoid arthritis
Correlation of coronary calcium calcification score and the FRS
The degree of coronary artery calcification (CAC) was calculated as described by Hoffmann et al (13). The area of each calcified plaque is multiplied by the peak radiological attenuation inside this area expressed as a coefficient (1 = an attenuation of 130 to 199 Hounsfield unit [HU]; 2 = 200 to 299 HU; 3 = 300 to 400 HU; and 4 = more than 400 HU). The sum of the scores for all coronary arterial lesions provides an overall score for each individual (15,16). A significant correlation was found when the calcium score was compared with the FRS (Figure 1).
Figure 1).
Correlation of the calcium score with the Framingham score in seven rheumatoid arthritis patients
The correlation analysis of the FRS and the clinical variables of the RA patients is presented in Table 6. Variables, such as age, BMI, the calcium score and the inflammatory markers (CRP and ESR) were found to significantly correlate with this score.
TABLE 6.
Spearman’s correlation between the Framingham risk score and clinical variables in patients with rheumatoid arthritis
| Clinical variables (n=43) | Spearman’s correlation, ρ | P |
|---|---|---|
| Age, years | 0.52 | <0.01 |
| Body mass index, kg/m2 | −0.30 | <0.05 |
| Disease duration, months | 0.05 | 0.75 |
| Systolic blood pressure, mmHg | 0.21 | 0.18 |
| Diastolic blood pressure, mmHg | 0.18 | 0.24 |
| Total cholesterol, mmol/L | 0.014 | 0.927 |
| CT Angio (calcium score) (n=6) | 0.86 | <0.05 |
| ESR, mm | 0.40 | <0.01 |
| CRP, ng/mL | 0.32 | <0.05 |
| HDL cholesterol, mmol/L | −0.28 | 0.06 |
| Triglycerides, mmol/L | 0.22 | 0.15 |
| DAS28 | 0.13 | 0.42 |
CT Angio Computed tomography angiography; CRP C-reactive protein; DAS28 Disease activity score of 28 joints; ESR Erythrocyte sedimentation rate; HDL High-density lipoprotein
Correlation of patient characteristics with HOMA-IR and HOMA-B detection
Table 7 summarizes the correlation between HOMA-IR and HOMA-B, and disease-specific parameters. Serum insulin levels were found to be highly significant, thus HOMA-IR was found to be significant. Parameters such as BMI, hypertension and CRP levels significantly correlated with HOMA-IR, but not HOMA-B, indicating that these risk factors of the metabolic syndrome may contribute to the occurrence of cardiovascular events observed in RA patients.
TABLE 7.
Correlation between patient characteristics and HOMA-IR and HOMA-B
| Parameter |
HOMA-IR
|
HOMA-B
|
||
|---|---|---|---|---|
| r | P | r | P | |
| Age, years | −0.298 | <0.05 | −0.179 | 0.257 |
| Disease duration, months | −0.185 | 0.235 | 0.114 | 0.474 |
| Body mass index, kg/m2 | 0.398 | <0.01 | −0.118 | 0.456 |
| Waist circumference, cm | 0.009 | 0.953 | 0.216 | 0.17 |
| Hypertension | 0.351 | <0.05 | 0.277 | 0.076 |
| CRP, ng/mL | 0.441 | <0.01 | −0.042 | 0.79 |
| DAS28 | 0.262 | 0.09 | 0.079 | 0.617 |
| ESR, mm | 0.261 | 0.09 | 0.022 | 0.89 |
Pearson’s correlation is represented by ‘r’. CRP C-reactive protein; DAS28 Disease activity score of 28 joints; ESR Erythrocyte sedimentation rate; HOMA-IR Homeostasis model of assessment of insulin resistance; HOMA-B Homeostasis model of assessment of beta-cell function
Comparison of the FRS in RA patients and healthy controls
The data in Table 8 shows that the FRS of the female RA population showed statistical significance when compared with healthy controls.
TABLE 8.
Comparison of the Framingham risk score in controls and rheumatoid arthritis (RA) patients
| Healthy controls (n=50) | RA patients (n=43) | P | |
|---|---|---|---|
| Total | 2.5±0.44 (0.5–13) | 1.8±0.33 (0.5–12) | 0.215 |
| Male | 4.97±0.85 (0.5–13) | 6±2.12 (5–12) | 0.677 |
| Female | 0.85±0.11 (0.5–3) | 1.37±0.21 (0.5–6) | <0.05 |
Data presented as mean ± SE (range)
Correlation of the calcium score with the FRS in RA patients
Figure 1 is a plot of calcium score versus FRS for seven RA patients. Calcium deposition was observed in only seven of the RA patients and demonstrated a linear correlation with FRS.
Correlation of DAS28 with components of the metabolic syndrome
Figure 2 shows the correlation of DAS28 with components of the metabolic syndrome. Group 1 consisted of patients with no components, while group 2 had either one or two components. Subjects in group 3 had more than three components, and the components of this group were found to statistically correlate with DAS28. Thus, the metabolic syndrome contributed to the disease activity status of the patients.
Figure 2).
Correlation of the disease activity score of 28 joints (DAS28) with components of the metabolic syndrome
DISCUSSION
We were able to identify important biological markers for easy and non-invasive identification of CVD in RA patients. Studies conducted in our laboratory on RA patients showed that factors such as RF isotypes (IgG, IgM and IgA), DAS28, the health assessment questionnaire for RA patients and inflammatory markers (CRP and ESR) were all found to be highly significant (P<0.001). Furthermore, older patients with high-grade inflammation demonstrated decreased beta-cell function. However, age was a significant factor for insulin resistance. Similar results were also shown by Ma et al (15), Dessein et al (16) and Jeppesen et al (17). Insulin resistance in RA patients was independently associated with markers of inflammation, disease characteristics and CAC. These results were in agreement with the published literature (18–21), in which these parameters were studied, and inflammation was suggested to play a central role in the development of atherosclerosis.
As shown in Figure 2, the components of the metabolic syndrome, especially those of group 3 patients, were found to statistically correlate with DAS28. Thus, the metabolic syndrome can also contribute to disease activity in RA patients. Similarly, we observed in our mixed-regression models for HOMA-IR in 43 RA patients that BMI and systolic blood pressure contribute to the determinants of insulin resistance. We found a linear relationship between the FRS and coronary artery atherosclerosis in RA patients.
No similar study on RA patients has been conducted in India to detect subclinical atherosclerosis. Our data indicated that an increase in RA disease severity was associated with a high prevalence and greater extent of CAC. Since the published literature shows inflammation in RA patients and CRP to be an inflammatory marker in cardiovascular disease, the authors proposed that the atherogenic effect seen in RA is due to inflammation. Age and sex differences in RA patients have been associated with an increased risk of subclinical atherosclerosis, independent of traditional risk factors, which are usually normal (22–24). Preventive measures should be taken especially in RA and younger patients who present with early signs of traditional risk factors; these results correlated with the study by Giles et al (25).
There was a significant correlation between the calcium score and the FRS in seven patients, which suggested an underlying risk of atherosclerosis. The graphical representation of the correlation of the calcium score with the FRS (Figure 1) shows calcium deposition in only seven RA patients. Therefore, RA patients are at an increased risk for multivessel cardiac artery disease, although the number of cardiovascular events were not increased in our study population. A comparison of the FRS in RA patients showed a score of 1.8±0.33, while that of controls was 2.5±0.44 – a difference that was not significant. When the score was compared separately in males and females, there was a significantly higher score in RA females compared with controls (1.37±0.21 versus 0.85±0.11; P<0.05). Coronary calcification had a sensitivity of 88% for patients with atherosclerotic disease and 97% for those with obstructive disease, with corresponding specificities of 55% and 41%, respectively. Coronary calcium sensitivity for detection of atherosclerotic disease in women younger than 60 years of age was 50%, significantly less than the 97% sensitivity in women older than 60 years of age and 87% sensitivity in men younger than 60 years of age (P<0.05 for each comparison). Logistic regression analysis revealed a 1.81-fold increase in the likelihood of detecting coronary calcification in the atherosclerotic lesions of men compared with those in women (95% CI 1.12 to 2.93; P=0.016). When controlled for age and severity of coronary disease for both sexes using angiography, CRP was significantly correlated with the Agatston score (age-adjusted Spearman’s correlation: 0.25 for men, 0.26 for women; both P<0.01). After adjustment for age and the FRS, the correlation remained significant (P=0.01) for both sexes. Further adjustment for BMI attenuated the correlation coefficient for women (0.14; P=0.09) but not for men (0.19; P<0.05) (26).
Women classified as ‘low risk’ based on the FRS with prevalent CAC had a higher risk for future CAD or CVD compared with low-risk women without detectable CAC (27). Prognostic value of CAC to predict future mortality is superior to the FRS. Addition of the CAC score to the FRS significantly improves the identification and prognostication of patients without known CAD (28).
The association between the FRS and additional CVD risk factors and RA-specific characteristics, such as cumulative exposure to corticosteroids and disease duration, is of interest, as is the association between the FRS and the severity of coronary calcification in patients with RA. However, although the FRS and the 10-year risk estimates were higher in patients with coronary calcification, the majority of patients with coronary calcification were classified as being at ‘low’ 10-year risk. To improve the prediction of future CVD in the general population, novel risk factors, such as the CAC score, have been studied.
Published RA literature report that circulating CD4+CD28null cells are increased and correlate with preclinical atherosclerotic disease and endothelial dysfunction. Such cells are also increased in the circulation and in plaques of patients with acute coronary syndrome, and possess endothelial cell cytotoxic activity (29). In healthy individuals, CD4+ CD28null T cells represent a minor subset, usually accounting for approximately 0.1% to 2.5% of the CD4+T cells. Aging, infections and chronic inflammation diseases are associated with the expansion of this peculiar T cell subset (30). In elderly individuals, CD4+CD28null T cells are used as a marker of immune response. Thus, the increased frequency in these subjects correlates with the development of autoimmune phenomenon and with defective B cell responses characterized by impaired production of antibodies. No studies on the T cell subpopulation were conducted in our laboratory.
RA patients fall into the intermediate 10-year risk category (ie, 10% to 20%) after being screened for CAD risk using traditional CAD risk factors. Using this risk-assessment tool would be a key step in managing CAD risk in RA patients. One validated method of assessing CAD risk is the Framingham model (30). Persons with low (<10%) FRSs do not benefit from aggressive risk factor modification, whereas those with high (>20%) FRSs do benefit (14).
Although CVD is a complex disease in the general population, it is more complex in RA patients. A range of traditional risk factors, nontraditional risk factors and inflammatory markers all contribute to cardiovascular mortality rates. Hence, comprehensive assessment of such traditional and nontraditional risk markers should form part of the routine care of RA patients at an early age.
CONCLUSIONS
We identified important biological markers for easy and noninvasive identification of CVD in RA patients.
We observed the relationship between the FRS and coronary artery atherosclerosis in RA patients.
Significant correlation between the calcium score and the FRS was observed in seven patients, suggesting an underlying risk of atherosclerosis.
Acknowledgments
The authors thank the Director and the Management of Sir HN Medical Research Society of Sir, HN Hospital and Research Centre, Mumbai, India, for a generous research grant to carry out this project, and the administrative staff for all the help rendered. The technical assistance of Ms Rashmi Shetty and Mr Umakant Nadkar for statistical analysis of data is also gratefully acknowledged. The authors also thank the staff of Jankharia Clinic, Mumbai, India.
Footnotes
AUTHOR CONTRIBUTIONS: Dr Deo had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Deo and Chogle were responsible for the study design, Dr Chogle and Ms Rashmi for the acquisition of data, Dr Deo, Ms Rashmi, Mr Umakant and Ms Mistry for laboratory testing, Mr Nadkar for statistical analysis, and Dr Deo for manuscript preparation and interpretation of data.
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