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The Journal of Clinical Endocrinology and Metabolism logoLink to The Journal of Clinical Endocrinology and Metabolism
. 2009 Dec 16;95(2):586–591. doi: 10.1210/jc.2009-1592

Associations among Metabolic Syndrome, Ischemia, Inflammatory, Oxidatives, and Lipids Biomarkers

Maria Gabriela Valle Gottlieb 1, Ivana Beatrice Mânica da Cruz 1, Marta M F Duarte 1, Rafael Noal Moresco 1, Mário Wiehe 1, Carla Helena Augustin Schwanke 1, Luiz Carlos Bodanese 1
PMCID: PMC2840868  PMID: 20016051

Abstract

Context: Metabolic syndrome (MS) is described as a cluster of cardiometabolic risk factors. Studies suggest that ischemia-modified albumin (IMA) is a biomarker of cardiovascular diseases. IMA levels could be associated with cardiometabolic risks and represent a possible indication of microvascular dysfunction in MS patients.

Objective: To confirm this possible association, we evaluated the association between IMA levels and MS.

Design: We performed a case-control study (32 healthy individuals and 74 subjects with MS) to evaluate the association between MS, IMA, and other biomarkers [high-sensitivity C-reactive protein (hs-CRP), oxidized low-density lipoprotein (OxLDL), oxidized low-density lipoprotein autoantibodies (anti-OxLDL), IL-6, lipid profile, and glucose].

Results: The MS group showed higher levels of IMA (0.618 ± 0.1355) as well as higher levels of hs-CRP, OxLDL, anti-OxLDL, and IL-6 than did control subjects (IMA = 0.338 ± 0.0486) (P < 0.01). Multivariate analysis showed that IMA and MS association was independent of sex, age, diabetes mellitus 2, and hypercholesterolemia.

Conclusion: We found an association between IMA and MS. Additional studies including prospective genetic variation approaches need to be performed to help elucidate this association between IMA and MS and its potential clinical role.

Higher concentrations of ischemia-modified albumin are associated with metabolic syndrome and other biomarkers that increase cardiovascular risk.

Metabolic syndrome (MS) describes a cluster of cardiometabolic risk factors that contribute to the accelerated development of atherosclerosis, coronary artery disease, and type 2 diabetes (1). Chronic hypertension and diabetes produce both macrovascular and microvascular pathophysiological changes, and therefore, a better understanding of the consequences of MS and diabetes in vascular physiology is of great importance (2). Indeed, diabetes markedly affects microcirculation as well as flow in large conduit arteries supplying vital organs such as the heart, brain, and kidney (3).

A growing number of studies suggest that ischemia-modified albumin (IMA) is a biomarker of cardiovascular diseases because the N terminus of this protein is damaged under conditions of ischemia and unable to bind metals. Previous studies have suggested that IMA is associated with acute ischemia (4,5), and its ability to discriminate myocardial infarction appears to be greater than that of C-reactive protein (CRP) (6). Investigations have demonstrated that serum IMA concentrations increase acutely after percutaneous coronary intervention in patients with spontaneous ischemia (7,8) and in patients with skeletal muscle ischemia. Additionally, it should be interpreted with caution in patients with peripheral vascular disease (9,10). Recent studies have associated increased levels of IMA with mortality in patients with end-stage renal disease (11), as a significant parameter in the early diagnosis of acute mesenteric ischemia (12), and as a powerful indicator of short-term mortality in ST-segment elevation myocardial infarction (13). Other prospective investigations found that the combination of heart-type fatty acid-binding protein and IMA measurements after initiation of chest pain may be highly effective for risk stratification in patients with acute coronary syndromes and normal cardiac troponin T levels (14). However, emerging investigations suggest that IMA is not only a marker of cardiac ischemia, as shown by Piwowar and collaborators (16) who studied the association between IMA levels and type 2 diabetes, and by our group in a study of the association between this biomarker and hypercholesterolemia (17). In both cases, diabetic and hypercholesterolemic patients, IMA levels were higher than in healthy subjects. These studies suggested that the albumin molecule in the plasma of diabetic patients is modified in the chronic hypoxia conditions provoked mainly by hyperglycemia and oxidative stress in diabetes.

Because a large number of cardiovascular patients have some cardiometabolic risk that pertains to MS diagnosis, we postulated here that IMA levels could be associated with these cardiometabolic risks and that elevated levels are a possible indication of microvascular dysfunction in MS patients. To confirm this possible association, we performed additional biochemical analyses of lipids and inflammatory markers previously found to be associated with MS.

Subjects and Methods

Study population

A case-control study was performed in Rio Grande do Sul, Brazil. Subjects were enrolled prospectively in this study from the Cardiology Service, Hospital São Lucas, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS) and the biochemical analysis laboratory (LABIMED Ltda). Subjects were enrolled in two groups, according to the presence of MS risk factors: 32 healthy individuals in the control group, and 74 individuals in the MS group. Mean age was 55.2 ± 8.8 yr for controls and 57.6 ± 8.3 yr for the MS group (P = 0.142). The sample included 34 men and 72 women. All patients were in a stable clinical status without signs of acute infections and acute ischemia. The control group consisted of healthy subjects with neither inflammatory states nor abnormalities in lipid and carbohydrate metabolism, as evidenced in routine medical checkups. We excluded subjects with hypoalbuminemia (<34 g/liter) and anemia because previous studies suggested their interference in IMA analysis (18,19,20). The Ethics Committee of PUCRS approved the study protocol (Protocol no. 07/044069). Informed consent was obtained from all individuals whose data were collected prospectively.

The diagnostic criteria for MS was made using the Third Report of the U.S. National Cholesterol Education Program Adult Treatment Panel (NCEP ATP III), following three or more criteria (21): abdominal obesity analyzed by waist circumference (men, >102 cm; women, >88 cm); triglycerides (≥150 mg/dl); high-density lipoprotein (HDL)-cholesterol (men, <40 mg/dl; women, <50 mg/dl); blood pressure (≥130/85 mm Hg); and fasting glucose (≥110 mg/dl). We also analyzed subjects with severe hypertension [systolic blood pressure (SBP) ≥160 mm Hg, and/or diastolic blood pressure (DBP) ≥100 mm Hg] and coronary disease, i.e. individuals with a previous diagnosis of acute myocardial infarct, angina, intermittent claudication, or stroke; and dyslipidemia, subjects with elevated total cholesterol, low-density lipoprotein (LDL)-cholesterol or triglyceride, as well as those who used cholesterol-lowering drugs. Details of these evaluations were given in a previous study by our group (22).

Biochemical determinations

Blood samples were collected after a 12-h overnight fasting by venous puncture into gray and red top Vacutainer (BD Diagnostics, Plymouth, UK) tubes with sodium fluoride plus potassium oxalate or no anticoagulant, respectively. Specimens were routinely centrifuged within 1 h of collection for 15 min at 2500 × g, and aliquots of serum samples were stored at −20 C for a maximum of 4 wk before IMA measurement. This procedure was performed because samples frozen at −20 C are stable, although IMA values have been reported to be slightly higher in stored vs. fresh samples (23). Plasma glucose, serum total cholesterol, and serum triglyceride concentrations were measured by standard enzymatic methods using Ortho-Clinical Diagnostics reagents in a fully automated analyzer (Vitros 950 dry chemistry system; Johnson & Johnson, Rochester, NY). HDL-cholesterol was measured in plasma supernatant after precipitation of apolipoprotein B-containing lipoproteins with dextran sulfate and magnesium chloride as previously described (24). LDL-cholesterol was estimated using the Friedewald equation (25). High-sensitivity CRP (hs-CRP) was measured by nephelometry (Dade Behring, Newark, DE). IL-6 was measured by capture ELISA, according to the manufacturer’s instructions (Biomyx Technology, San Diego, CA). Oxidized LDL (OxLDL) was also determined by capture ELISA according to the manufacturer’s instructions (Mercodia AB, Uppsala, Sweden), as described by Holvoet et al. (26). OxLDL autoantibodies (anti-OxLDL) were determined using ELISA as described by Wu and Lefvert (27). Serum IMA was measured in nondiluted samples by a colorimetric assay previously described by Bar-Or et al. (28) on a Cobas Mira Plus Instrument, according to the method described by Fagan et al. (29) and validation described by Gidenne et al. (30). This method consisted of adding 50 μl of 0.1% cobalt chloride (CoCl2 · 6H2O; Sigma, St. Louis, MO) in H2O to 200 μl of serum, gently mixing, and waiting 10 min for adequate albumin-cobalt binding. Fifty microliters of dithiothreitol (1.5 mg/ml H2O; Sigma) were added for color development, and the reaction was quenched 2 min later by adding 1.0 ml of 0.9% NaCl. All incubations were performed at 37 C. Absorbance was read in a spectrophotometer at 470 nm (Hitachi U-2800A; Hitachi High-Technologies Corporation, Tokyo, Japan), using a serum-cobalt blank without dithiothreitol, and the results were reported in absorbance units (ABSU). The colorimetric assay format quantitatively measures unbound cobalt remaining after albumin-cobalt binding has occurred. Thus, with reduced albumin-cobalt binding, there is more unbound cobalt, resulting in an elevated absorbance. IMA assay was standardized in the Department of Pharmaceutical Science, and a standard curve was prepared in the range of 6.0–60.0 g CoCl2/ml. One IMA unit was defined as “grams of free” Co (II) in the reaction mixture per milliliter of serum sample. The assay was linear within this range. Interassay coefficient of variance to test the reproducibility was calculated by repeating a patient sample (IMA 15.6 units), six assays in duplicate, and was found to be less than 15%, which was slightly on the high side but within acceptable levels. These conditions were similar to those described previously by Chawla et al. (31). Strict attention to sample handling procedures was given in experimental procedures to maintain consistency of the analysis (30).

Statistical analysis

Statistical analysis was performed using the SPSS/PC statistical package, version 12.0 (SPSS, Inc., Chicago, IL). Data were analyzed statistically by Student’s t test to determine the differences between case-control groups. Multivariate analysis was performed to analyze the possible intervenient effects of gender, age, and MS variables diagnosis (waist circumference, glucose, SBP, DBP, triglycerides, and HDL-cholesterol on IMA and MS association. The intervenient effects of other biomarkers analyzed here in the MS and IMA association was also evaluated as well as the effect of type 2 diabetes mellitus (16) and hypercholesterolemia (17). We performed these last analyses because previous studies showed association between IMA and type 2 diabetes mellitus as well as hypercholesterolemia. Body mass index (BMI) is not included in MS diagnosis criteria; however, because obesity can cause hypoxia states, we performed a multivariate analysis to observe the possible influence of obesity evaluated by BMI in IMA and MS association. Statistical analyses were performed where all P values were two-tailed, and P < 0.05 was considered statistically significant.

Results

Baseline characteristics of case-control study subjects are shown in Table 1. As expected, the MS group had significantly higher levels of BMI, SBP, DBP, total cholesterol, LDL-cholesterol, and triglycerides. The only variable that did not show significant differences between the case-control groups was HDL-cholesterol. IMA, hs-CRP, OxLDL, anti-OxLDL, and IL-6 levels were significantly higher in MS than control subjects, as seen in Table 2.

Table 1.

Baseline characteristics of study participants

Variable Groups
P
Control MS
n 32 74
Gender
 Males 11 (34.4) 20 (27.0) 0.595
 Females 21 (65.6) 54 (73.0)
BMI (kg/m2) 22.1 ± 4.6 32.6 ± 6.1 0.0001
Waist circumference (cm) 78.8 ± 7.9 107.2 ± 12.3 0.0001
SBP (mm Hg) 117.5 ± 8.0 147.8 ± 26.8 0.001
DBP (mm Hg) 74.6 ± 18.5 85.9 ± 15.9 0.01
Glucose (mg/dl) 81.7 ± 7 133.7 ± 68.7 0.001
Total cholesterol (mg/dl) 148.5 ± 17.8 200.4 ± 58.1 0.001
HDL-cholesterol (mg/dl) 50.5 ± 9.3 48.2 ± 12.9 0.371
LDL-cholesterol (mg/dl) 78.2 ± 11.5 114.4 ± 49.5 0.001
Triglycerides (mg/dl) 99.4 ± 43.5 214.9 ± 34.8 0.001
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Data are expressed as number (percentage) or mean ± sd. The statistical comparison was performed by Student’s t test. 

Table 2.

IMA and lipid and inflammatory biomarkers in MS and healthy controls

Variable Groups
P
Control MS
IMA (ABSU) 0.338 ± 0.0486 0.618 ± 0.1355 0.0001
hs-CRP (mg/dl) 0.172 ± 0.0716 1.721 ± 0.964 0.0001
IL-6 (pg/ml) 17.06 ± 3.17 53.20 ± 14.52 0.0001
OxLDL (mg/dl) 0.193 ± 0.261 0.662 ± 0.461 0.0001
anti-OxLDL (mg/liter) 3.359 ± 2.277 27.822 ± 17.010 0.001
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Data are expressed as mean ± sd. The statistical comparison was performed by Student’s t test. 

Multivariate analysis showed that the association between IMA and MS was independent of sex, age, and MS diagnostic criteria (Table 3) and independent of hs-CRP, OxLDL, anti-OxLDL and IL-6 (Table 3). Additional multivariate analysis showed that IMA and MS association was independent of type 2 diabetes mellitus (Wald = 21.268; P > 0.0001) and hypercholesterolemia (Wald = 21.268; P < 0.0001).

Table 3.

Multivariate analysis of MS parameters and IMA levels and lipid and inflammatory biomarkers

Variables Wald P
Analysis 1
 IMA (ABSU) 43.798 >0.0001
 Sex 0.272 0.602
 Age (yr) 1.551 0.213
 HDL-cholesterol (mg/dl) 0.201 0.674
 Triglycerides (mg/dl) 31.214 >0.0001
 Glucose (mg/dl) 13.443 0.0001
 Waist circumference (cm) 31.883 >0.0001
 SBP (mm Hg) 18.127 >0.0001
 DBP (mm Hg) 2.943 0.086
Analysis 2
 IMA (ABSU) 30.555 >0.0001
 Sex 0.819 0.365
 Age (yr) 1.907 0.167
 hs-CRP (mg/dl) 11.676 0.001
 OxLDL (mg/dl) 15.772 >0.0001
 Anti-OxLDL (mg/dl) 29.022 >0.0001
 IL-6 (pg/ml) 36.996 >0.0001
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Analysis 1 included in logistic regression analysis IMA, age, sex, and main MS diagnosis parameters. Analysis 2 included age, sex, and oxidative and inflammatory biomarkers. 

In our control subjects, we did not include the obese (BMI >30 kg/m2). However, in the MS group, eight (10.8%) had a BMI below 25 kg/m2; 25 (33.8%) were overweight (BMI >25 kg/m2 but <30 kg/m2); and 41 (55.4%) were obese (BMI >30 kg/m2). When we compared the IMA levels just in the control group, considering BMI, we did not find statistical differences (<25 kg/m2 = 0.335 ± 0.049, and overweight = 0.355 ± 0.045; P = 0.398). Similarly, when we compared the IMA levels just in the case group, considering BMI, we did not find statistical differences (<25 kg/m2 = 0.625 ± 0.120; overweight = 0.572 ± 0.203; obese = 0.645 ± 0.0598; P = 0.477). Additionally, the Pearson correlation between IMA and BMI in the MS case group as well as in the control group was not significant (r2 = 0.013, P = 0.944; and r2 = −0.31, P = 0.865, respectively).

Multivariate regression showed that the association between higher IMA levels and MS was independent of sex, age, obesity, and variables associated to MS diagnosis.

A multivariate analysis to see whether the significance of increased IMA levels would be maintained after correcting for BMI was performed. Statistical significance was maintained after this correction (IMA Wald = 12.394, P = 0.001; BMI Wald = 3.866, P = 0.049). Additionally, we performed a statistical analysis considering BMI stratification in each group (control and MS) separately. In the control group, five subjects were overweight (BMI >25 kg/m2 but <30 kg/m2), and 27 had BMI values below 25 kg/m2. Statistical analysis showed similar IMA values in these groups (<25 kg/m2 = 0.335 ± 0.049; overweight = 0.355 ± 0.454; P = 0.398). Because the number of overweight subjects was very low, a Pearson correlation analysis between IMA and BMI values was performed in the control group. We did not observe a significant correlation (r2 = 0.013; P = 0.944). Therefore, in our sample, the IMA levels showed an association with MS independent of BMI.

Discussion

We describe here an association between IMA levels and MS in subjects without acute ischemia.

The biological explanation of this association is related to a decrease in tissue oxygen perfusion, triggering albumin modification. Here, we analyzed the possible association of IMA levels and MS that did not present an acute biological condition, as myocardial infarction, but a microenvironment that could increase tissue hypoxia. The MS subjects presented higher IMA levels that could indicate an important sub-clinical condition of a peripheral oxygenation insufficiency and a low-grade inflammatory state. This possible association is corroborated to higher oxidative and inflammatory biomarkers as hs-CRP, OxLDL, anti-OxLDL, and IL-6 found in our sample.

The role of microenvironment alteration in the increase of IMA values was corroborated in recent studies, for example Serné et al. (32), who suggested that microvascular dysfunction, which plays a role in regulating coronary blood flow, is a potential pathophysiological mechanism of MS. In this case, microvascular dysfunction would be the underlying mechanism for the associations between hypertension, obesity, and impaired insulin-mediated glucose availability. This hypothesis was corroborated by Pirat et al. (16), who found an impaired coronary flow reserve associated to MS.

An additional question that we explored in this study is whether higher IMA levels could be related to BMI values. Unfortunately, our control sample did not include obese subjects because we looked for an association between MS and IMA levels. For this reason, we performed additional statistical analysis, considering BMI stratification, and our results suggested that IMA and BMI values are not independent related to MS. However, we cannot rule out a possible association between obesity and IMA levels in subjects without other MS diagnostic parameters. Therefore, this question needs to be studied further in complementary investigations.

It is important to ponder some considerations associated with our methodological design. We conducted an exploratory case-control study with a relatively small number of subjects. However, a primary limitation of the present study is its cross-sectional design and the inherent possibility that genetic and/or lifestyle factors may have influenced the results described here. Our research group, for example, has reported previous findings suggesting an association between overweight/obesity or MS and genetic polymorphism involving oxidative, lipid, and vascular metabolism (22). In an effort to minimize confounding variables, we studied subjects of similar age and nonsmokers who were not currently taking medication that, could influence inflammatory and oxidative markers (i.e. statins). Additionally, all MS subjects included in this study had a similar level of routine physical activity (considered sedentary subjects) and were seen by a medical service associated with a cardiology service. Healthy control subjects were also evaluated and did not show any dysfunction or MS-related morbidity.

Other important intervening variables affecting IMA levels could be lipid levels, such as triglycerides. Investigations suggest that triglycerides have primarily a storage function with toxicity resulting mainly from long-chain nonesterified fatty acids and their products such as ceramides and diacylglycerols. Because the MS criteria include higher triglyceride levels, this variable could potentially interfere with IMA levels. However, in a previous study performed by Gidenne et al. (31), no significant interference with IMA levels was observed for triglyceride levels. Our previous study that analyzed the IMA values between normolipid and hypercholesterolemic subjects corroborated these data because we did not find a positive association between triglycerides and IMA levels.

In conclusion, our population-based data show that higher concentrations of IMA are associated with MS and other biomarkers that increase cardiovascular risk. Because metabolic risk factors are highly prevalent in patients with acute coronary diseases, to clarify whether the higher IMA levels found in these subjects could be influenced by the presence of preexisting metabolic risk factors such as MS, it is of fundamental importance to perform studies with a large sample.

Acknowledgments

The authors thank the team of the Cardiology Service of the Pontifical Catholic University of Rio Grande do Sul and the LABIMED Ltda., located in Santa Maria, Brazil. Dr. A. Leyva provided English editing of the manuscript.

Footnotes

Sources of funding: Conselho Nacional de Desenvolvimento Científico e Tecnológico–CNPq (No. 471233/2007-2; No. 311231/2006-3; No. 3081.009087/2008-99), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-CAPES (166/08), and Fundação de Amparo à Pesquisa do Rio Grande do Sul FAPERGS (grants and fellowships).

Disclosure Summary: The present study does not have real or apparent conflicts of interest.

First Published Online December 16, 2009

Abbreviations: ABSU, Absorbance units; anti-OxLDL, OxLDL autoantibodies; BMI, body mass index; CRP, C-reactive protein; DBP, diastolic blood pressure; HDL, high-density lipoprotein; hs-CRP, high-sensitivity CRP; IMA, ischemia-modified albumin; LDL, low-density lipoprotein; MS, metabolic syndrome; OxLDL, oxidized LDL; SBP, systolic blood pressure.

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