European Journal of Cardiovascular Medicine

Metabolic syndrome (MetS) , a cluster of interconnected factors that directly increases the risk of coronary heart disease (CHD), other form of cardiovascular atherosclerotic diseases and T2DM, is characterised by dyslipidemia, elevated arterial blood pressure , dysregulated glucose homeostasis, abdominal obesity and insulin resistance.1It has been hypothesized that the state of chronic low-grade inflammation associated with the excess of adipose tissue explained the development of obesity related pathologies, such as T2DM and cardiovascular disease. This may be mediated by the increased secretion of pro- inflammatory cytokines by the adipose tissue.² Other factors such as chronic oxidative stress and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis can also be involved in its pathologinesis.¹

Interleukin-18 (IL-18), discovered by Okamura H et al. as an interferon-gamma– inducing factor, is a member of the interleukin 1 family and has been suggested as a strong pro-inflammatory cytokine potentiating the differentiation of T-lymphocytes and NK cells of the immune system and also stimulating the production and secretion of other cytokines,

chemokines and adhesion molecules.^3,4 It is produced by many cell types as inactive proIL-18 which is activated by enzyme caspase-1.⁵

IL-18 polymorphism may be associated with the increased serum IL-18 levels, impaired insulin sensitivity and increased risk of having the metabolic syndrome.⁶ It stimulates both type 2 helper T (Th 2 ) and IL-2 response and may act synergistically with IL-12 to stimulate type 1 helper T cells (Th1) response with the production of IFN-γ ,which is a central feature in the development of atherosclerotic lesion.⁷ This synergistic effect is due to IL 12 which induce the α chain of the IL-18 receptor in lymphocytes whereas in non-T cells such as macrophages, the IL-18 receptor is constitutively expressed.^8,9 Several cross sectional studies reported higher circulating IL-18 in patients with type-2 diabetes mellitus which suggested IL-18’s contribution to microangiopathy such as nephropathy in type 2 diabetes.^10-13

The study has been done to compare the circulating Interleukin-18 Levels in male and female population having MetS and compare it with controls and also to see the association of IL-18 levels with MetS.

Study populations: A total of 50 patients aged 18 years and above with MetS identified using IDF (2006) criteria and 50 age and sex matched normal healthy individuals were included in the study. This cross-sectional study was carried out in the Department of Biochemistry in collaboration with the Department of Medicine, Regional Institute of Medical Sciences (RIMS), Imphal, for a period of two years from November 2021 to October 2023.

Exclusion criteria: Patients with malignant diseases, hypothyroidism, severe renal insufficiency, chronic liver disease, used of hepatotoxic drugs and statins, known cases of autoimmune and inflammatory diseases and history of alcohol addiction.

This study was approved by the Research Ethics Board, Institutional Ethics Committee (IEC), Regional Institute of Medical Sciences (RIMS), Imphal.

Blood sample collection and laboratory measurements: After an overnight fasting for 8 hours, 5 ml of blood samples were collected from the antecubital vein in the early morning. Out of the blood drawn, 2ml of blood was collected in fluoride vial for fasting blood glucose, and the remaining blood transferred to plain vial for the estimation of serum lipid level and serum interleukin-18. The sample is centrifuged for 10 minutes at 3000 rpm within 30 mins of collection. All the lipid tests and fasting blood glucose estimation were carried out on the same day. Serum for interleukin-18 estimation was immediately stored in aliquots at-200C. Serum lipid profile estimation was done by Enzymatic Colorimetric test with lipid clearing factor (LCF). Fasting blood sugar estimation was done by enzymatic colorimetric test for glucose method without deproteination. Estimation of interleukin level was done by ELISA method using Human IL-18 sandwich ELISA kit.

Metabolic syndrome is defined according to IDF criteria, which require a waist circumference (WC) ≥ 90cm in men or 80 cm in women (for Asian population) plus any two or more of the following risk factors: serum triglycerides (TG) ≥150mg/dl, serum HDL < 40mg/dl in men, <50mg/dl in women, blood pressure ≥130/85 mmHg or treatment of previously diagnosed hypertension and fasting plasma glucose ≥ 100 mg/dl or previously diagnosed diabetes mellitus.¹³

Statistical analysis

Statistical analysis were carried out with IBM SPSS version 21 for windows. Continuous variables were given a mean ± SD (if normal distribution) and were compared using Student’s t-test. The correlation between IL-18 and different components of the MetS and BMI were calculated using Pearson’s coefficient analysis. The results were evaluated within 95% confidence interval (CI) and at a significance level of two-sided p-value less than 0.05.

Study populations: A total of 50 patients aged 18 years and above with MetS identified using IDF (2006) criteria and 50 age and sex matched normal healthy individuals were included in the study. This cross-sectional study was carried out in the Department of Biochemistry in collaboration with the Department of Medicine, Regional Institute of Medical Sciences (RIMS), Imphal, for a period of two years from November 2021 to October 2023.

Exclusion criteria: Patients with malignant diseases, hypothyroidism, severe renal insufficiency, chronic liver disease, used of hepatotoxic drugs and statins, known cases of autoimmune and inflammatory diseases and history of alcohol addiction.

This study was approved by the Research Ethics Board, Institutional Ethics Committee (IEC), Regional Institute of Medical Sciences (RIMS), Imphal.

Blood sample collection and laboratory measurements: After an overnight fasting for 8 hours, 5 ml of blood samples were collected from the antecubital vein in the early morning. Out of the blood drawn, 2ml of blood was collected in fluoride vial for fasting blood glucose, and the remaining blood transferred to plain vial for the estimation of serum lipid level and serum interleukin-18. The sample is centrifuged for 10 minutes at 3000 rpm within 30 mins of collection. All the lipid tests and fasting blood glucose estimation were carried out on the same day. Serum for interleukin-18 estimation was immediately stored in aliquots at-200C. Serum lipid profile estimation was done by Enzymatic Colorimetric test with lipid clearing factor (LCF). Fasting blood sugar estimation was done by enzymatic colorimetric test for glucose method without deproteination. Estimation of interleukin level was done by ELISA method using Human IL-18 sandwich ELISA kit.

Metabolic syndrome is defined according to IDF criteria, which require a waist circumference (WC) ≥ 90cm in men or 80 cm in women (for Asian population) plus any two or more of the following risk factors: serum triglycerides (TG) ≥150mg/dl, serum HDL < 40mg/dl in men, <50mg/dl in women, blood pressure ≥130/85 mmHg or treatment of previously diagnosed hypertension and fasting plasma glucose ≥ 100 mg/dl or previously diagnosed diabetes mellitus.¹³

Statistical analysis

Statistical analysis were carried out with IBM SPSS version 21 for windows. Continuous variables were given a mean ± SD (if normal distribution) and were compared using Student’s t-test. The correlation between IL-18 and different components of the MetS and BMI were calculated using Pearson’s coefficient analysis. The results were evaluated within 95% confidence interval (CI) and at a significance level of two-sided p-value less than 0.05.

A total of 100 subjects were enrolled in the present study, out of which 50 were healthy controls and 50 subjects with MetS. There were 23 males and 27 females in control group and 20 males and 30 females in the case group. The age group of 41-50 years have the maximum number of MetS patients. The details of baseline socio-demographic and biochemical variables are presented in Table -1. The mean ages of healthy controls and MetS subjects were 41.28 ±11.96 and 44.10 ±10.59 years, respectively. The mean values of BMI, abdominal circumference, SBP, DBP, FBS, TG and IL-18 were significantly higher(p<0.05) in cases in both the males and females while HDL-C is significantly lower(p<0.05) in them.

Figure 1 shows that the mean serum IL-18 levels was higher among the obese when compared to control. Further it shows that the serum IL-18 level was highest in obese with MetS cases (271.60 ± 24.32 pg/dl) when compared to those who were obese without MetS(212.71± 35.20 pg/dl).

The ROC curve shows that the IL-18 could be used to predict MetS. The optimal threshold and area under the curve (AUC) are >231.4 and 0.943 (95% CI 0.894 to 0.992, p- value=0.001), respectively (Figure-2). Additionally, the percentage of sensitivity, specificity, PPV and NPV of the IL-18 are 90%, 86%, 86.5% and 89.6%, respectively (Table-2)

The results of Pearson’s correlation analysis between IL-18 and different components of the MetS and BMI are presented in Table-3. Significant positive corraelation was observed with abdominal circumference, TG, FBS, DBP, and BMI whereas significant negative correlation was observed with HDL. SBP was not significantly correlated with IL-18 levels.

The simple logistic regression shows that BMI, IL-18 and among the components of MetS, abdominal circumference and HDL were the most significant predictors of MetS in the cases (p-<0.05) as seen from Table 4.

Table 1: Baseline characteristics of study subjects (N=100)

Figure-1: Mean serum IL-18 between controls, obese with MetS and Obese without MetS

Figure 2: ROC curve of serum IL-18 level for the prediction of metabolic syndrome

Table 2: Receiver operator characteristic analysis results for IL-18 in serum and cut-off point analyses for IL-18

Table 3: Correlations between IL-18 and different components of the MetS and BMI

Table 4: Logistic regression of serum IL-18 with MetS components and BMI

Dependent variable: Metabolic syndrome

The major findings of the present study are that elevated IL-18 is an independent risk factor for the MetS and it has significant positive correlation with the components of MetS, namely waist circumference, TG, FBS, DBP and BMI while negative correlation with HDL among the cases. It also shows that both the male and female subjects with MetS have significantly higher IL-18 than the subjects without MetS.

As a pleiotropic proinflammatory cytokine, IL-18 contributes early to the cascade of inflammation by stimulating the production of tumor necrosis factor-α and secondarily IL-6.¹⁴ Its role in plaque destabilization may be due to its high expression in atherosclerotic plaque which suggests a link between MetS syndrome and atherosclerosis.¹⁵ Other preliminary study reported that IL-18 polymorphism influenced IL-18 levels leading to low- grade inflammation which is made worsen by elevated TNF-α. All these factors increased the risk of developing MetS.¹⁶

Obesity is a low grade chronic inflammation characterised by hypertrophic adipocyte along with the immune cells, mostly macrophages, to infiltrate the defective adipose tissue of the obese people.¹⁷The production of anti-inflammatory, insulin-sensitizing adipokines like adiponectin is decreased in conjunction with an increase in the secretion of pro-inflammatory cytokines including TNFα, IL-6, and IL-1β.¹⁸ People with the metabolic syndrome are demonstrated to have elevated levels of IL-18, and these levels rise in the blood as the components of the syndrome increase.^19,20 The association between IL-18 and cardio metabolic health is further supported by its unsurprising associations with dyslipidemia, and its capacity to predict cardiovascular mortality.^21,22 Cornier MA et al in their study found that IL-18 is positively associated with BMI, WC, TG, SBP and DBP, fasting glucose and insulin, and negatively associated with HDL-C in a nondiabetic population.²³

According to the current study, the optimal cut off value for serum IL-18 in distinguishing non-metabolic and metabolic syndrome participants was 231.4 ng/ml, with a sensitivity of 90 % and a specificity of 86%. Nedeva I et al determined that IL-18 ≥ 235 pg/ ml had 63% sensitivity, 51% specificity for determining subjects with disturbances of glycemic regulation and a 62 % sensitivity and 54 % specificity for determining those with MetS.²⁴ Yamaoka-Tojo M et al observed that elevated levels of circulating IL-18 were linked to elevated MetS scores and systemic inflammation, regardless of the existence of diabetes or dyslipidemia.²⁵ The present study also observed IL-18 as an independent risk factor for MetS. Esposito et al. discovered that acute hyperglycemia in humans increased IL-18 levels via an oxidative process.²⁶ Several study limitations are acknowledged. As the study is a single centered cross- sectional study, the causal relationship of IL-18 and MetS could not be established. Further large scale clinical studies are needed to be established.

The result of this study confirmed the association of the components of the MetS with raised serum IL-18.. Thus it can be concluded that high serum IL-18 may be used as a biomarker to screen and identify the risk of developing MetS and thus further prevent the incidence of its complication viz, type 2 diabetes and cardiovascular disease.

Acknowledgements

The authors thank the patients for their participation in the study.

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