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INTRODUCTION
Obesity is an important health problem with huge dimensions (1), leading to a metabolic dysfunction. The adipose tissue is a storage organ, but the role of adipose tissue as an endocrine organ has emerged (2). Adipokines are secreted by different cells of this tissue such as adipocytes, macrophages, mast cell and stromal vascular. These adipokines could be related with the pathogenesis of insulin resistance, hypertension, dyslipemia and other cardiovascular risk factors related with obesity (3) and in this context, omentin-1 is one of them.
Omentin-1 is a 32 kDa protein that is secreted by stromal vascular cells in visceral adipose tissue, and it is expressed in other tissues such as lung, heart and placenta (4). This adipokine is a beneficial molecule that improve insulin-stimulated glucose uptake and triggers Akt pathway, which produces downstream effects such as glucose metabolism (5). Circulating omentin-1 correlated negatively with anthropometric parameters such as weight, body mass index (BMI), waist circumference and biochemical parameters (fasting insulin, HOMA-IR and leptin) and positively with high density lipoprotein cholesterol (HDL-C) and adiponectin levels (6).
Metabolic syndrome (MS) is a constellation of risk entities related with obesity, including glucose intolerance or diabetes mellitus, abdominal obesity, hyperlipidemia and high blood pressure levels (7). MS is considered a polygenic and multifactorial disorder due to interaction of numerous genes with environmental factors and in this context, adipose tissue develops an important role in the presence of this entity (8). Adipose tissue dysregulation and altered secretion of different adipokines are presented in this syndrome (9,10). Moreover, few studies have evaluated the relationship between MS and circulating levels of omentin-1 in obese patients without cardiovascular events (11-13), this type of MS without cardiovascular events or diabetes mellitus is called nascent MS. For example, Jialal et al. (12) reported lower levels of omentin-1 in patients with MS than in patients without MS. This study was realized in a small sample of 75 subjects, of which 30 had nascent MS. In other small sample of 93 adults, Vu et al. (13) reported an association between this adipokine and MS only in males. These preliminary findings have not been evaluated in large samples of patients that represent the wide range of patients with obesity.
The aim of our investigation was to evaluate the potential relationship between circulating omentin-1 levels with nascent MS and its components in an important sample of Caucasian patients with obesity.
MATERIALS AND METHODS
SUBJECTS AND PROCEDURE
This cross-sectional study was performed in a population of 606 Caucasian patients with obesity (20 to 70 years) of age remitted to our Nutritional Unit in a Health Area of the Castilla y León Autonomous Community in Spain. Consecutive volunteers with body mass index (BMI) ≥ 30 kg/m2 were included. The inclusion criteria for the study protocol were the following — body mass index ≥ 30 kg/m2 and an age in the range 20-70 years. Exclusion criteria were any of the next conditions: diabetes mellitus, cardiovascular events, chronic kidney disease, chronic liver disease, heart failure, malignant tumours and history of alcoholism, or use of medications that potentially influenced weight or metabolic parameters (statins, fibrates and drugs against diabetes mellitus or hypertension). Finally, all patients provided their written and informed consent, and the protocol complied with the Declaration of Helsinki as well as with local institutional guidelines. It was approved by the hospital’s Ethics Committee (code of registration 06/2021).
Demographic and clinical characteristics of all patients were recorded in the hospital registry system. The parameters of the present study included sociodemographic data, classical anthropometric parameters (weight, height, body mass index (BMI) and waist circumference), total fat mass (FM) by bioimpedance, blood pressure, and biochemical assessment. During the baseline visit 15 ml of venous blood after an 8 hour overnight fast were aliquoted in ethyllenediaminetetraacetic acid (EDTA)-coated tubes for biochemical analysis. The Adult Treatment Panel III (ATPIII) criteria: elevated fasting glucose or treatment for diabetes mellitus, elevated triglycerides (> 150 mg/dl), low HDL cholesterol < 40 mg/dl (males) or < 50 mg/dl (females), elevated systolic or diastolic blood pressure (> 130/85 mmHg) and increased waist circumference (> 88 cm in females and > 102 cm in males) were used to diagnosis nascent MS. Patients meeting at least 3 of these above-mentioned criteria were included in the MS+ group and those not meeting these criteria in the MS- group.
ANTHROPOMETRIC PARAMETERS AND BLOOD PRESSURE
Height and weight measurements were performed while patients were wearing light clothes and no shoes. Body height (cm) was determined using a standard height measurement scale (Omrom, LA, CA, USA) and body weight was measured using digital scales (Omrom, LA, CA, USA). Body mass index (BMI) was calculated using the formula (weight (kg) / height2 (m)). Waist circumference was measured at the nearest 0.1 cm just above the ilium with a flexible standard tape (Omrom, LA, CA). Body fat mass was determined by impedance with an accuracy of 50 g (14) (EFG BIA 101 Anniversary, Akern, It).
Finally, systolic and diastolic blood pressures were measured two consecutive times on the right arm after 10 minutes rest at the heart level with and automated monitor (Omrom, LA, CA, USA), and the average of both measures was calculated.
BIOCHEMICAL PROCEDURES
Serum biochemistry analyses for glucose, insulin, C-reactive protein (CRP), total cholesterol, HDL-cholesterol, triglyceride, and interleukine-6 were realized using the COBAS INTEGRA 400 analyser (Roche Diagnostic, Basel, Switzerland). LDL cholesterol was calculated using Friedewald’s equation (LDL cholesterol = total cholesterol - HDL cholesterol – triglycerides / 5) (15). Based on these parameters, the homeostasis model assessment for insulin resistance (HOMA-IR) was obtained using these values (glucose (mml/L) x insulin (IU/L) / 22.5) (16). The triglyceride glucose index (TyG) was calculated using the formula: ln(fasting TG (mg/dl) x fasting blood glucose (mg/dl) / 2) (17).
STATISTICAL ANALYSIS
All statistical data were analyzed using the SPSS ver.23 (IBM) software (SPSS Inc. Chicago, IL). Sample size (n = 600) was calculated to find a difference in omentin-1 levels greater than 50 ng/ml between the two groups of patients (MS- vs. MS+). The normality of the variables was tested using the Kolmogorov-Smirnov test. Mean ± standard deviation was used to express continuous variables. Categorical variables were presented as percentages. Continuous variables were compared with Student’s t-test (for normally distributed variables) or the Mann-Whitney U-test (for non-normally-distributed variables). Differences between categorical variables were determined using the Chi-squared test. The relationship between omentin-1 levels and other variables was evaluated using Pearson´s correlation analysis. A multivariate logistic regression analysis was performed using a backward stepwise method to identify independent variables for MS. The Receptor Operation Characteristic Curve for MS was used to determine the best cutoff point of omentin-1 in predicting MS. And the cutoff points were elucidated by two methods: the area under the curve (AUC) that had the best specificity and sensitivity values for the test in question, and the Youden index as (sensitivity + specificity) - 1). p-values below 0.05 were considered statistically significant.
RESULTS
A total of 606 Caucasian patients with obesity were evaluated, 150 males (24.8 %) and 456 females (75.3 %) with an average age of 49.3 ± 13.3 years (range: 31-68). A total of 307 subjects had MS (49.2 %) and 299 did not show MS (50.8 %). Mean age in the metabolic syndrome (MS+) group was higher (50.6 ± 3.9 years vs 45.9 ± 6.2 years: p = 0.02) than in the non-metabolic syndrome group (MS-). The proportions of females were higher in both groups (MS+ group, 24.7 % males vs 75.3 % females; p = 0.01, and MS- group, 24.6 % males vs 75.4 % females; p = 0.02). No differences in the percentages of both groups were detected.
The basic demographic and clinical characteristics of the population are showed in table I. We reported statistical differences (delta; p-values) between both groups in BMI (3.1 ± 0.2 kg/m2; p = 0.02), body weight (8.8 ± 2.1 kg; p = 0.03), body fat mass (5.0 ± 0.2 kg; p = 0.03) and waist circumference (11.6 ± 2.5 cm; p = 0.02). All these parameters were higher in MS+ group than MS- group. Systolic blood pressure (6.3 ± 2.6 mmHg; p = 0.01) and diastolic blood pressure (6.5 ± 2.1 mmHg; p = 0.02) were higher in the MS+ group than in the MS- group, too.
Table I. Basic demographic and clinical characteristics of the Caucasian patients with obesity.
BMI: body mass index; DBP: diastolic blood pressure; SBP: systolic blood pressure; WC: waist circumference. Statistical differences between groups (p < 0.05).
Laboratory findings according to MS group are summarized in table II. We observed higher levels in the MS+ group than in the MS- group in the following parameters (delta; p-values): fasting glucose (16.0 ± 2.9 mg/dL; p = 0.01), HDL-cholesterol (-3.5 ± 0.3 mg/dl; p = 0.03), triglycerides (31.1 ± 4.5 mg/dl; p = 0.01), insulin levels (4.1 ± 0.4 UI/L; p = 0.02), HOMA-IR (1.8 ± 0.3 units; p = 0.03), omentin-1 levels (78.0 ± 13.8 ng/ml; p = 0.01) and TyG index (0.50 ± 0.01 mg/dl; p = 0.02). Total cholesterol, LDL-cholesterol, and CRP levels were similar in both groups.
Table II. Laboratory findings of Caucasian patients with obesity (mean ± SD).
HOMA-IR: homeostasis model assessment of insulin resistance; CRP: C-reactive protein; TyG: triglyceride glucose index. Statistical differences between groups (p < 0.05).
Table III shows the percentage of each metabolic syndrome criterion in the MS+ group vs the MS- group. As expected, the percentages of central obesity, hypertriglyceridemia, low-HDL cholesterol, hypertension and hyperglycemia were higher in the MS+ group than in the MS- group. Omentin-1 levels according to the number of MS criteria decreased as the number of criteria were aggregated (0 criteria, 715.4 ± 13.2 ng/ml; 1 criterion, 533.5 ± 12.2 ng/ml; 2 criteria, 520.6 ± 11.1 ng/ml; 3 criteria, 511.8 ± 9.1 units; 4 criteria, 488.1 ± 8.2 units, and 5 criteria, 452.1 ± 8.1 ng/ml; p = 0.001).
Table III. Metabolic syndrome and components of metabolic syndrome in Caucasian patients with obesity.
The following cutoff points were used for the criteria of: central obesity (waist circumference > 88 cm in females and > 102 in males), hypertension (systolic BP > 130 mmHg or diastolic BP > 85 mmHg or specific treatment), hypertriglyceridemia (triglycerides > 150 mg/dl or specific treatment) or hyperglycaemia (fasting plasma glucose > 110 mg/dl). Statistical differences between groups (p < 0.05).
Table IV describes correlations between different parameters and omentin-1 levels. A negative correlation was observed between omentin-1 and adiposity parameters, glucose, insulin, HOMA-IR, TyG index and triglycerides in both groups. And a positive correlation was observed between omentin-1 and HDL-cholesterol, too.
Table IV. Correlation analysis of omentin with other parameters.
CRP: C-reactive protein; HOMA-IR: homeostasis model assessment. Statistical differences between groups (p < 0.05).
The multivariate logistic regression analysis was performed including variables with p < 0.25 between groups in the univariate analysis but not showing collinearity and excluding variables used as criteria of MS. BMI (OR = 1.17, 95 % CI = 1.09-1.31; p = 0.02), HOMA-IR (OR = 5.21, 95 % CI = 1.69-21.11; p = 0.01) and omentin-1 (OR = 0.95, 95 % CI = 0.94-0.97; p = 0.02) remained in the final model as independent predictors of MS.
The ROC curve of the omentin-1 for MS is shown in figure 1. The area under the curve (AUC) according to ATPIII criteria showed a value of 0.721 (0.694-0.792: p = 0.001). The cut-off point according to the Youden index was 372.45 ng/ml of omentin-1 to predict MS, with a sentivity and specificity of 80.9 % and 70.2 %, respectively.
DISCUSSION
In our study, patients with obesity and nascent MS had significantly lower levels of omentin-1 compared with patients without MS. In all patients omentin-1 levels showed a significant negative correlation with insulin resistance as estimated by HOMA-IR and TyG index, adiposity parameters and triglyceride levels. A positive correlation with HDL-cholesterol was observed, too.
In small previous studies, Jialal et al. (12) showed that the adipose tissue of patients (n = 45) with nascent MS secreted lower omentin-1 levels than the adipose tissue of patients (n = 30) without MS. To our knowledge, this is the first study to validate these findings in an important sample of Caucasian patients with obesity, and to give a cut-off value of omentin-1 to predict nascent MS. Similar to our study, other study demonstrated lower levels of omentin-1 in patients with nascent MS compared with patients without MS (18). This work was carried out in a different sample than ours, composed of a sample of 110 Turkish patients with MS, all with high blood pressure. In other small sample of 93 adults, Vu et al. (13) reported an association between this adipokine and MS only in males. In comparison with these above-mentioned investigations, decreased circulating omentin-1 in subjects with MS in our study were more pronounced. This relationship has also been found in studies carried out with obese adolescents (19), but in the literature there are also studies that have demonstrated a lack of difference in the levels of omentin-1 depending on the presence or absence of MS (20). These contradictory results depended on age, gender distribution, average BMI, ethnic diversity, study design, exclusion and inclusion criteria, heterogeneity or predominance of MS components, and measurements techniques.
In addition to the difference in omentin-1 levels depending on the presence of MS in our obese patients, we also demonstrated a significant inverse correlation between insulin resistance estimated as TyG index and HOMA-IR. It has been postulated that omentin-1 contributes to insulin sensitivity through the modulation of protein kinase (Akt/protein kinase B). In one study, HOMA-IR was related to decreased circulating omentin-1 levels (21), and these results were replicated with TyG, too (12). Another design showed that weight loss with different hypocaloric diets produced parallel significant decreased values of omentin-1 and insulin resistance (22).
In addition, we reported that levels of omentin-1 were inversely correlated with adiposity parameters (BMI, fat mass and waist circumference). Obesity is a well-known chronic low-grade inflammatory condition and may change circulating adipokine levels secondary to adipocyte dysregulation in visceral adipose tissue. This increase of visceral adipose tissue has been related with a decrease in omentin-1 gene expression (23). However, there are discrepancies between studies investigating this relationship and some of them failed to detect this correlation (24). These inconsistencies raise the question of whether omentin-1 levels are regulated by the obesity status or by the inflammation process triggered by obesity.
The positive correlation between HDL cholesterol and omentin-1 has been previously reported in different studies (25). A potential explanation for this association is that dysregulation of omentin-1 may adversely affect insulin signaling and regulation, thereby modifying HDL production (26). Some studies have explained the potential protective role of omentin-1 concentrations against coronary artery disease through this association with HDL-cholesterol (27).
There were some limitations to our study. First, the study has been designed in Caucasian adults with obesity, so the data are not generalizable to younger subjects, overweight patients, or other ethnicities. Secondly, the design as a cross-sectional design (transversal) does not allow to extract causality. Third, we did not directly measure the visceral distribution of fat, only indirect parameters such as waist circumference were used. Fourth, patients with diabetes mellitus were not included. However, patients with impaired glucose tolerance may have been enrolled in this design as oral a glucose tolerance test was not carried out as routine screening test, and this fact may affect the findings. Finally, physical activity has not been evaluated, and it has a potential role in omentin-1 levels (28). The strengths of our study were that we studied a representative population of obese patients with a median age of predominantly females.
The results from our design showed that Caucasian patients with obesity had clearly lower serum omentin-1 levels in the presence of nascent MS. An inverse correlation was demonstrated with adiposity parameters, insulin resistance and triglycerides, with direct correlation with HDL-cholesterol. All this allows to consider that omentin-1 may play a partial role in the development of MS and may be a predictive marker of MS and metabolic health status, too (29).
