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Abstract

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Objective

To examine low-density lipoprotein (LDL) size, LDL susceptibility to oxidation, and plasma insulin levels in children with systemic lupus erythematosus (SLE).

Methods

Fifty-nine SLE patients and 59 healthy, age-matched control subjects were studied. LDL size was determined by gradient gel electrophoresis. LDL oxidizability was assessed by lag time for conjugated diene formation during copper incubation. Plasma levels of fasting insulin, glucose, lipids, lipoproteins, apolipoproteins B and A-I, and fatty acids were also measured.

Results

Compared with control subjects, SLE patients showed significantly higher plasma insulin levels and increased susceptibility of LDLs to oxidation. Patients with active disease were more likely than patients with inactive disease or control subjects to have the following lipid characteristics: small, dense LDL subclass, elevated total cholesterol levels, elevated LDL cholesterol levels, elevated triglyceride levels, and low levels of high-density lipoprotein cholesterol (HDL-C). Statistically significant direct correlations were observed between disease activity and triglyceride levels and between disease activity and lag time, whereas significant inverse correlations were found between disease activity and HDL-C levels and between disease activity and LDL size. Prednisone dosage explained only 15.6% of the variance in insulin levels.

Conclusion

SLE patients have higher plasma insulin levels and increased LDL oxidizability compared with healthy control subjects. These abnormalities may contribute to the accelerated atherosclerosis observed in patients with SLE.

Myocardial infarction, cerebrovascular events, and subclinical atherosclerosis are increasingly recognized as serious complications of systemic lupus erythematosus (SLE) (1, 2). The etiology and pathogenesis of atherosclerosis in SLE are multifactorial. Abnormal plasma concentrations of lipids and lipoproteins are common in adults and children with SLE (3, 4) and may contribute to the atherogenic process in this disease. Other lipoprotein features, not usually measured in clinical laboratories, may also participate in the development and progression of atherosclerosis in these patients.

Low-density lipoproteins (LDLs) are heterogeneous in size, density, lipid composition, and possibly atherogenicity (5, 6). Using nondenaturating gradient gel electrophoresis to analyze LDL particle size distribution, Austin et al (7) identified 2 LDL subclass patterns. LDL subclass pattern A is characterized by a predominance of LDL particles >25.5 nm, and LDL subclass pattern B is characterized by a predominance of smaller (≤25.5 nm), denser LDLs. Individuals with small, dense LDLs have been found to have a higher risk for coronary artery disease (8–10). The presence of LDL pattern B is commonly associated with higher plasma triglyceride and apolipoprotein B (Apo B) levels and lower levels of high-density lipoprotein cholesterol (HDL-C) (11); these are the most characteristic lipid abnormalities found in SLE patients (3, 4). A similar dyslipidemia has been observed in patients with insulin resistance (12). Furthermore, there is evidence to support the possibility that LDL oxidizability is increased in patients with insulin resistance (13). Taken together, these data suggest that the dyslipoproteinemia observed in SLE patients resembles the abnormalities reported in subjects with insulin-resistant states.

No previous study has investigated LDL particle size and susceptibility of the LDL to oxidative modification in patients with SLE, and there is only 1 report, in abstract form (14), describing hyperinsulinemia and insulin resistance in adult women with SLE. Accordingly, the present study was designed to examine the size and oxidizability of LDLs and the fasting insulin levels in pediatric SLE patients and age-matched control subjects.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Study population.

Fifty-nine consecutive SLE patients younger than 17 years, who were attending the outpatient pediatric rheumatology clinic at the General Hospital of the National Medical Center “La Raza” (Mexico City, Mexico), were enrolled. All fulfilled the American College of Rheumatology criteria for the classification of SLE (15). No patient had clinical evidence of diabetes, thyroid dysfunction, or severe liver disease. Because kidney involvement may affect insulin sensitivity (16), LDL size (17), and oxidative stress (18), 10 patients with renal disease, defined as proteinuria >0.5 gm/24 hours or hematuria >10 red blood cells/high-power field (15), were excluded. None of the patients were pregnant at the time of the study. Of the 59 patients studied, 7 were boys (mean ± SD age 14.6 ± 2.07 years) and 52 were girls (age 13.8 ± 3.02 years). All consumed their usual diet during the study. The control group consisted of 59 healthy adolescents (52 girls and 7 boys); all were volunteers from a high school, who took part in a school program screening for cardiovascular risk factors. Similar proportions of female patients (75.0%) and female controls (80.8%) had undergone menarche. The patients and controls were similar in age, weight, and height distribution. A parent of each child signed the consent form for participation. The protocol was approved by the Institutional Review Board of our hospital.

Patient characteristics and clinical assessment.

Patients and controls were instructed to avoid strenuous exercise and to eat a light dinner the day before the study began and blood was withdrawn. For all children, height, weight, waist and hip circumferences, and blood pressure were assessed. Body mass index (BMI) was calculated by dividing weight by height squared (kg/m2).

Disease activity was assessed using the Mexican modification of the Systemic Lupus Erythematosus Disease Activity Index (MEX-SLEDAI) (19). Based on the MEX-SLEDAI at the time of evaluation, 15 patients were considered to have active disease (MEX-SLEDAI ≥6) and 44 had inactive disease (MEX-SLEDAI <2). The mean ± SD age was 12.53 ± 2.85 years in the group with active disease and 14.32 ± 2.83 years in the group with inactive disease.

Hyperinsulinemia was defined as a fasting plasma insulin level ≥9.85 μU/ml. This definition was obtained by using the 75th percentile value from a Mexican population sample of 455 healthy adolescents (20). LDL subclass B was considered to be present when particle size was ≤25.5 nm (7). Hypercholesterolemia was defined as a total cholesterol (TC) level of ≥200 mg/dl or low-density lipoprotein cholesterol (LDL-C) level of ≥130 mg/dl. Hypertriglyceridemia was defined as a triglyceride level of ≥130 mg/dl, and hypoalphalipoproteinemia as a HDL-C level of <35 mg/dl (21).

At the time of study, 12 (80%) of the 15 SLE patients with active disease were taking prednisone at a median dosage of 17.5 mg/day (range 2.5–50), and 6 (40%) were taking chloroquine at a median of 150 mg/day (range 75–150). Of the 44 patients with inactive disease, 35 (80%) were taking prednisone at 7.5 mg/day (range 1.25–75.0), and 28 (64%) were taking chloroquine at 150 mg/day (range 37.5–150). Of the 47 patients taking prednisone, 28.8% were taking at least 15 mg/day.

Laboratory assessment.

Fasting blood samples were obtained from an antecubital vein after subjects had been seated for 15 minutes. A tourniquet was used but was released before withdrawal of blood into vacuum tubes (Vacutainer; Becton-Dickinson, Mountain View, CA) containing EDTA. Plasma was separated from blood cells by centrifugation, and aliquots were stored at –70°C. Lipids and glucose were measured in fresh plasma. Total cholesterol and triglycerides were measured by enzymatic methods (Roche-Syntex/Boehringer Mannheim, Indianapolis, IN). HDL-C was quantified after precipitation of lipoproteins containing Apo B with phosphotungstate/Mg2+. LDL-C levels were estimated by using the Friedewald formula as modified by DeLong et al (22). Intraassay coefficient of variation (CV) values for TC, triglyceride, and HDL-C levels were 0.43%, 0.89%, and 1.72%, respectively; and the interassay CV values were 1.76%, 2.03%, and 3.24%, respectively. Accuracy and precision in our laboratory were under periodic surveillance by the Centers for Disease Control and Prevention service (Atlanta, GA).

Lipoprotein(a), Apo B, and Apo A-I levels were measured by kinetic nephelometry (Beckman Instruments, Irvine, CA). Intra- and interassay CVs for lipoprotein(a) concentrations were <8%. Glucose levels were determined by the glucose oxidization method. Fasting insulin was measured by a radioimmunometric assay (Coat-A-Count; Diagnostic Products, Los Angeles, CA); the intra- and interassay CVs were 2.1% and 6.8%, respectively. LDL subclasses were determined by a modification of the method of Krauss and Burke (5). Briefly, 2–14% gradient electrophoresis was performed under nondenaturating and nonreducing conditions. Electrophoresis was performed for 20 hours at 150V in a Mighty Small SE 245 chamber (Hoefer Scientific Instruments, San Francisco, CA). The gels were analyzed with a densitometer (model 620; Bio-Rad, Hertfordshire, UK), using the Bio-Rad Molecular Analyst program (version 1.1). Particle size was calibrated using LDL subfractions whose molecular diameter had been determined by analytic ultracentrifugation (courtesy of Dr. R. Krauss, Donner Laboratories, Berkeley, CA). To obtain the calibration graph, latex beds (38 nm) and the following high molecular weight proteins (all from Pharmacia, Piscataway, NJ) were used as standards: thyroglobulin (17 nm), apoferritin (12.2 nm), and catalase (6.2 nm). Intra- and interassay CVs were 0.66% and 1.46%, respectively.

For analysis of LDL oxidation, a plasma aliquot containing butyl-hydroxytoluene (BHT) as antioxidant was stored in N2 at –70°C. LDL particles were separated by ultracentrifugation at 4°C using standard methods. Susceptibility to oxidation was determined by the method described by Esterbauer et al (23), with minor modifications (24). The LDL lag time, defined as the interval between the addition of Cu2+ and the beginning of rapid oxidation, was determined by the intersection of the baseline with the tangent of the propagation phase (23) and is expressed in minutes. For analysis of plasma fatty acids (performed in 51 patients and in all 59 control subjects), a 100-μl sample was used for the extraction of lipids as described by Folch et al (25). Briefly, to 100 μl of plasma containing 0.005% BHT, 50 μg of heptadecanoic acid was added as an internal control. The extraction of total lipid fraction was performed using a mixture of chloroform and methanol (2:1 by volume). The total lipids extracted were esterified to their fatty acid methyl esters as described by Christie (26). Fatty acid methyl esters were separated and identified by gas liquid chromatography in a Fratovap 2300 chromatograph (Carlo Erba, Milan, Italy), fitted with a 25m × 0.25 mm (internal diameter) fused-silica capillary column coated with CP-Sil 88 (film thickness 0.25 nm), at an isotherm temperature of 195°C and helium gas at a flow rate of 1 ml/minute.

Statistical analysis.

Central tendency and dispersion measurements were estimated. Student's t-test was used to compare results in patients and controls. Proportions were tested using the chi-square test. Spearman's correlation analysis was used to test for the association of disease activity assessed by MEX-SLEDAI, prednisone dosage, chloroquine dosage, and insulin levels (as continuous variables) with metabolic measures and LDL size. Independence of associations of disease activity, prednisone dosage, chloroquine dosage, age, sex, menstrual status, renal function (creatinine clearance), BMI, and waist circumference with insulin levels, LDL size, and susceptibility to oxidation was determined by multiple regression analysis. All values are expressed as the mean ± SD. P values less than 0.05 were considered significant. Statistical analysis was performed using SPSS version 10 software (SPSS, Chicago, IL).

RESULTS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Demographic, metabolic, and physiologic characteristics of the patients with SLE and the controls are shown in Table 1. Of note, the 12 patients not treated with prednisone had higher fasting insulin levels (mean ± SD 12.8 ± 5.3 μU/ml versus 8.9 ± 4.0 μU/ml; P = 0.007) and an increased prevalence of hyperinsulinemia (66.7% versus 28.8%; P = 0.013) than the healthy controls. Compared with control subjects, patients with SLE had significantly higher levels of diastolic blood pressure, triglycerides, and plasma insulin concentrations and lower Apo A-I levels. When patients were subclassified according to disease activity, those with active disease showed significantly (P = 0.001) smaller LDL size (25.4 ± 0.9 nm) than those with inactive disease (26.7 ± 1.4 nm) or controls (26.7 ± 1.0 nm). Although the group of SLE patients as a whole had similar LDL size and their plasma was richer in saturated and monounsaturated fatty acids and had lower levels of polyunsaturated fatty acids compared with control subjects, their LDL particles were significantly more susceptible to oxidation, as indicated by the shorter lag time.

Table 1. Anthropometric, Physiologic, and Metabolic Characteristics of SLE Patients and Control Subjects*
VariableSLE (n = 59)Control (n = 59)P
  • *

    Values are the mean ± SD. P values were determined by Student's t-test. SLE = systemic lupus erythematosus; BMI = body mass index; SBP = systolic blood pressure; DBP = diastolic blood pressure; TC = total cholesterol; HDL-C = high-density lipoprotein cholesterol; TG = triglycerides; LDL-C = low-density lipoprotein cholesterol; Apo = apolipoprotein; Lp(a) = lipoprotein(a); SFA = saturated fatty acid; MUFA = monounsaturated fatty acid; PUFA = polyunsaturated fatty acid.

  • Plasma fatty acids were analyzed in 51 patients.

Age, years13.8 ± 213.4 ± 00.256
BMI, kg/m221.7 ± 421.0 ± 30.269
Waist, cm73.1 ± 1070.7 ± 70.156
SBP, mm Hg111.4 ± 15109.1 ± 110.378
DBP, mm Hg75.1 ± 1464.0 ± 7<0.001
TC, mg/dl159.8 ± 52154.2 ± 280.476
HDL-C, mg/dl44.2 ± 1345.0 ± 80.697
TG, mg/dl138.6 ± 10091.4 ± 340.001
LDL-C, mg/dl93.3 ± 4194.6 ± 250.840
Apo A-I, mg/dl108.3 ± 22124.9 ± 18<0.001
Apo B, mg/dl79.2 ± 3571.6 ± 170.141
Lp(a), mg/dl20.3 ± 2515.4 ± 160.231
Glucose, mg/dl85.4 ± 1686.5 ± 70.615
Insulin, μU/ml13.7 ± 88.9 ± 4<0.001
Lag time, minute−162.4 ± 1677.3 ± 260.001
LDL size, nm26.3 ± 126.7 ± 10.138
SFA, %37.9 ± 434.0 ± 3<0.001
MUFA, %24.47 ± 321.5 ± 2<0.001
PUFA, %37.0 ± 444.1 ± 3<0.001

Figure 1 shows the prevalence of lipoprotein abnormalities, LDL subclass B, and hyperinsulinemia in SLE patients and in control subjects. Hypercholesterolemia, assessed by either TC or LDL-C, hypertriglyceridemia, hypoalphalipoproteinemia, and LDL subclass B were significantly more common in the patients with active disease than in the group with inactive disease or control subjects. Hyperinsulinemia was more prevalent in SLE patients, but a significant difference was observed only between patients with inactive disease and controls.

thumbnail image

Figure 1. Prevalence of lipoprotein abnormalities, low-density lipoprotein (LDL) subclass B, and hyperinsulinemia in systemic lupus erythematosus (SLE) patients and control subjects. TC = total cholesterol; LDL-C = LDL cholesterol; TG = triglyceride; HDL-C = high-density lipoprotein cholesterol. ∗ = P < 0.05 versus SLE patients with active disease; ∗∗ = P < 0.05 versus SLE patients with inactive disease.

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The associations of disease activity assessed by MEX-SLEDAI, prednisone dosage, chloroquine dosage, and insulin levels (as continuous variables) with metabolic measures and LDL size were examined by Spearman's correlation analysis. Disease activity was associated with HDL-C level (r = –0.290, P < 0.05), triglyceride level (r = 0.395, P < 0.001), and LDL size (r = –0.377, P < 0.01). Prednisone dosage was related to insulin level (r = 0.279, P < 0.05), TC level (r = 0.288, P < 0.05), triglyceride concentration (r = 0.451, P < 0.01), and lag time (r = –0.312, P < 0.05). A significant inverse association was observed between chloroquine dosage and TC level (r = –0.335, P < 0.01), LDL-C level (r = –0.300, P < 0.05), and Apo B level (r = –0.263, P < 0.05). Insulin levels were associated with triglyceride concentrations (r = 0.311, P < 0.05). Plasma fatty acid distribution was not associated with any variable. Multiple regression analysis (Table 2) was used to determine the independence of these associations. Disease activity, chloroquine dosage, prednisone dosage, age, sex, menstrual status, renal function (creatinine clearance), BMI, and waist circumference were entered into the model as independent variables and lag time, LDL size, and insulin levels were entered as dependent variables. Disease activity accounted for 6.0% of the variance in lag time and 10.7% of the variance in LDL size. Prednisone dosage had a positive association with insulin level, explaining 15.6% of its variance.

Table 2. Results of Multiple Linear Regression Analyses with Biochemical Measures as Dependent Variables in Patients with Systemic Lupus Erythematosus*
Dependent variableIndependent variableβR2, %P
  • *

    Model included the following independent variables: Mexican modification of the Systemic Lupus Erythematosus Disease Activity Index (MEX-SLEDAI), prednisone dosage, chloroquine dosage, body mass index, waist circumference, age, sex, menstrual status, and renal function; those for which statistical significance was reached are shown. β = standardized coefficient; R2 = adjusted variance as explained by the variable in the model; LDL = low-density lipoprotein.

Lag timeMEX-SLEDAI0.2806.00.044
LDL sizeMEX-SLEDAI−0.35510.70.012
Insulin levelPrednisone dosage0.41615.60.002

DISCUSSION

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Our results in a pediatric SLE population without renal disease confirmed the abnormal lipid profile described previously (3, 4). The novel findings of our investigation were the significantly reduced size of LDL particles and the increased prevalence of LDL subclass B in patients with active SLE. Also, we found that LDLs from patients had increased susceptibility to oxidation. In addition, the results showed that plasma insulin concentrations were higher in patients with active or inactive disease than in healthy controls.

Although we did not use the euglycemic hyperinsulinemic clamp method to assess insulin sensitivity, fasting insulin levels have been shown to closely correlate with results obtained using this reference method (27). The finding of high insulin levels in our pediatric patients is consistent with the results of a recent study reported in abstract form (14), showing reduced insulin sensitivity and increased insulin concentrations in adult women with SLE. Modest elevations of insulin concentrations similar to those observed in our study have been found to impair endothelial function, probably by increasing oxidant stress (28), and may therefore play a major role in triggering and sustaining atherogenesis (29).

With regard to the reasons for the elevated insulin levels in SLE patients, diet composition and medications commonly used for SLE treatment may be participating factors. The type of dietary fatty acids may influence insulin action (30), and one way to monitor the type of fat in the diet is to record the fatty acid composition in plasma (31). A recent study (32) showed that saturated fatty acids in plasma were negatively related to insulin sensitivity, whereas polyunsaturated fatty acids had a positive relationship to insulin action. In our study, plasma saturated fatty acid levels were significantly higher and polyunsaturated fatty acids significantly lower in SLE patients compared with control subjects, indicating a fatty acid pattern in plasma that would favor insulin resistance. However, no relationship between plasma fatty acid composition and insulin levels was found.

On the other hand, glucocorticoids are known to induce insulin resistance (33), and we found a significant independent association between prednisone dosage and insulin levels. It is therefore possible that prednisone therapy might partially account for the elevated insulin concentrations in our SLE patients. However, it seems unlikely that steroid treatment is an important determinant of hyperinsulinemia because fasting insulin levels and the prevalence of hyperinsulinemia were also higher in the 12 patients who were not receiving prednisone, compared with control subjects.

There might be several alternative explanations for elevated fasting insulin levels in patients with SLE. For instance, moderately elevated levels of anti-insulin antibodies have been observed in nondiabetic patients with SLE (34). In a more recent study (35), the frequency of IgM anti-insulin antibodies in SLE patients was significantly higher than in healthy controls and comparable with that in patients with type 1 diabetes. Moreover, levels of C-reactive protein and other markers of inflammation are elevated in SLE patients (36), and there is evidence for a role of inflammation in the development of insulin resistance and hyperinsulinemia in nondiabetic women (37). It is therefore possible that anti-insulin antibodies and chronic inflammation described in SLE patients may play a role in the high insulin levels observed in this study.

Prospective studies have demonstrated that small, dense LDL particle size is an independent risk factor for future cardiovascular events (8–10). In this study, SLE patients with active disease had smaller LDL particles compared with patients with inactive disease and control subjects. Of greater interest, however, is the finding that patients with inactive disease, despite having normal LDL size, also showed greater LDL oxidation than controls. The greater oxidative susceptibility of LDLs in our patients is in accordance with the results of studies suggesting that LDL oxidizability is increased in insulin-resistant subjects (13), and also with reports of increased formation of free radicals (38) and elevated serum levels of lipid peroxidation products, such as 4-hydroxynonenal (39) and 8-epi–prostaglandin F (18), in patients with SLE. Moreover, elevated concentrations of autoantibodies against oxidized LDLs in patients with SLE have been described (40). A recent study (36) showed that anti–malondialdehyde LDL and anti–oxidized LDL antibodies of IgG type appear to discriminate between female SLE patients with cardiovascular disease and age-matched female SLE patients without manifest cardiovascular disease, with the former group having higher concentrations of these antibodies. Together, these findings indicate that in SLE there is a pro-oxidant environment in which LDL particles may be more easily oxidized, and that modified LDLs may have an important role in the atherosclerotic process of this disease.

In summary, patients with SLE have markedly higher rates of coronary heart disease than controls, and these increased rates are only partly explained by the increased levels of conventional cardiovascular risk factors. Our study demonstrates an increased preponderance of small, dense LDLs in patients with active disease, and high fasting insulin levels and increased LDL oxidizability in patients with active or inactive disease. Oxidized LDL has proinflammatory and atherogenic properties. Therefore, we conclude that hyperinsulinemia and increased levels of oxidative stress with accompanying increased LDL oxidation may underlie some of the increased risk for cardiovascular disease in patients with SLE.

REFERENCES

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES
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