The metabolic syndrome (MetS) is a constellation of cardiometabolic risk factors, adiposity and insulin resistance being its main features. The presence of MetS increases risk of coronary heart disease and type 2 diabetes mellitus (T2DM)1. Although the pathogenic mechanisms of MetS have not been elucidated, both increased inflammation and insulin resistance play a pivotal role. It seems that the monocyte/macrophages and adipose tissue (AT) interact to accentuate both the pro-inflammatory state and increased insulin resistance. There is a marked increase in macrophages and crown-like structures in the subcutaneous adipose tissue (SAT) of patients with MetS2. Adipose tissue production of cytokines (adipokines or adipocytokines) plays central role in MetS and T2DM1. Adipokines play a critical role in storage, food intake, energy expenditure, and lipid and glucose metabolism3. In MetS there is an increase in plasma leptin, plasminogen activator inhibitor-1, retinol-binding protein-4(RBP-4), chemerin, serum amyloid-A, C-reactive protein (CRP), interleukin-1, -6, -8, lipopolysaccharide, fetuin A (FetA) and a decrease in adiponectin and omentin-2.
The growing evidence shows that the processes resulting in T2DM are started very early with a long lag phase between the disease onset and the clinical diagnosis. Multiple researches have evaluated various serum biomarkers as predictive for T2DM4–5. Nearly 40% of the proteins that have been suggested to be candidate markers for diseases such as cancer, cardiovascular disease, and stroke can be found in whole saliva. With numerous plasma biomarkers verified for metabolic risk, relatively few studies have been carried in the area of salivary biomarkers. It has been observed that approximately 40% of cancer, stroke and cardiovascular disease biomarkers are present in whole saliva6.Finally it should be noted that 27% of the salivary proteome overlapped with the plasma proteome6. Human saliva is a rich reservoir of biomarkers including over 3652 proteins and 12,562 peptides and shares nearly 51% of proteins with the serum proteome and 79% of peptides with the serum peptidome5. Periodic evaluation of select plasma protein biomarkers during time course of type 2 diabetes mellitus (T2DM) development may increase the predictive ability of diabetes risk scores7. The use of salivary biomarkers has increasing value as a result of discovery of significant similarities between the salivary and serum proteomes7. The collection of saliva is a noninvasive, easily repeatable and less stressful technique than blood withdrawal. As an example, the levels of salivary resistin, visfatin, and adiponectin correlated with serum hormonal levels8. As an example, a recent meta-analysis of biomarkers in periodontitis and/or obesity demonstrated that, obesity and periodontitis, together or separately, are associated with altered serum and gingival crevicular fluid levels of leptin, adiponectin, and resistin, but concluded that the role of vaspin, omentin-1 and some other molecules, which can be key points underlying the association between obesity and periodontitis, remains to be further investigated9.
In this research we focused on adipose- and/or skeletal muscle-derived signaling as examples of metabotrophic factors (MTFs) involved in the pathogenesis of obesity and related cardiometabolic diseases9. Hence collectively a battery of proportionally associated with insulin resistance related adiposity and cardiometabolic risk factors. Hence it was the aim of this study to examine the early cardiometabolic risk associations of these peptides; namely Lipocalin, Nesfatin, Omentin, Oxytocin, RBP-4 (retinol-binding protein-4), Resistin, SIRT 1 (sirtuin 1), Visfatin and ZBED3 (zinc finger, BED-type (ZBED) protein 3) with adiposity – and atherogenecity –related insulin resistance in normoglycemic and dysglycemic metabolic syndrome population. Scarcity of studies that investigated correlations between plasma and salivary cardiomatabolic biomarkers’ levels in MetS patients is clearly noticeable. Moreover given that saliva biomarkers seem to be promising in the area of metabolic syndrome (MetS) detection and diagnosis due to less invasive nature, less expensive and faster sample collection in comparison to plasma biomarkers10. Taken together it was this study aim to investigate the potential correlations between plasma and saliva levels of these cardiometabolic risk biomarkers for pharmacotherapy institution and follow up reasons of MetS patients with a defined cluster of adiposity and atherogenecity indices.
Lipocalin 2 is a 25 kDa glycoprotein expressed in several cells as in adipocytes transporting small lipophilic ligands, as in lipopolysaccharides, through hydrophilic body fluid11–12. It can be a pro-inflammatory factor elevated in obese ⁄ inflammatory states11 secreted by White adipose tissue (WAT).13 In addition lipocalin 2 is involved in apoptosis, ion transport, inflammation, cell survival, tumorigenesis, reproduction and atherosclerosis12. Nesfatin is an anorexic neuropeptide of significant regulation of energy metabolism and food intake and widely distributed in the central nervous system and peripheral tissues. It is linked to regulation of food intake and lipid metabolism, inhibiting fat accumulation, accelerating lipid decomposition, and in inhibiting the development of lipid-related disorders of obesity and metabolic syndrome (MetS)14. Furthermore it influences cardiac functions –related glycemia and generates weight loss15. Lower levels of nesfatin (pg/mL) were reported in both pre-diabetic and non-diabetic MetS patients16–17.
Omentin is 313 amino acids-adipocytokine expressed by a diversity of tissues (as in mesothelial cells, vascular cells, airway goblet cells, omental and epicardial fat, small intestine, colon, ovary, and plasma). It sustains body metabolism and insulin sensitivity, with antiinflammatory, anti-atherosclerotic, and cardiovascular protective effects via AMP-activated protein kinase/Akt/nuclear factor-κB/mitogen-activated protein kinase (ERK, JNK, and p38) signaling.18 In a close-relation with T2DM;12 this visceral adipokine expression in pre)adipocytes is decreased by glucose/insulin and stimulated by fibroblast growth factor-21 and dexamethasone. It can also enhance insulin-mediated glucose uptake in human subcutaneous and omental adipocytes19. It was reported to increase insulin sensitivity by activating Akt and enhancing insulin-(but not basal) stimulated glucose uptake both by subcutaneous and omental adipocytes; due to lack of intrinsic insulin-mimetic activity12. Significantly salivary and serum Omentin-1 were found related in chronic periodontitis and T2DM20.
Oxytocin (OXT) is involved in the maintenance of labor and lactation in female reproduction. It has substantial roles in regulating social memory and anxiety21. It is principally a nanopeptide released by paraventricular nucleus (PVN), and the supraoptic nucleus (SON) in the hypothalamus. With pronounced regulatory roles in energy homeostasis as an anorexigenic factor; low OXT circulating concentrations were found in diet-induced or genetically modified animal models of obesity and in humans.22–23 In amenorrheic athletes; OXT secretion proportionally correlated with measures of energy availability in linkage to weight and body mass index and energy expenditure.22 OXT receptors are found in multiple organs as in uterus, breast, aorta, and esophagus24. OXT receptors over-expression in close linkage to adiposity and lipolysis in adipocytes was inherently noticeable.24–25 In MetS and prediabetes; it was pronouncedly reduced.26–28 Meanwhile salivary OXT positively associated with plasma, but not with urine OXT in women acutely ill with anorexia nervosa.29
Retinol-binding protein 4 (RBP-4) is one of the most important adipokines that affects systemic insulin sensitivity and glucose homeostasis with link to insulin resistance and MetS in obesity30. It is a transport protein for vitamin A (retinol), synthesized mainly by hepatocytes followed by adipocytes12. RBP-4 may play a role in the pathogenesis of T2D by participates in the development of insulin resistance by impairing insulin signaling at both the receptor and post-receptor levels, as well as by stimulation of liver gluconeogenesis31. RBP-4 is potentially associated with an increased risk of developing cardiovascular disease, particularly among patients with obesity, mainly due to an increased expression of pro-inflammatory cell surface adhesion molecules and soluble pro-inflammatory factors and possibly due to an unfavorable lipid profile and an increased intima-media thickness32. Resistin is secreted as a 94-amino acid polypeptide with an inhibitory effect on adipocyte differentiation and an association with insulin resistance12. Human resistin is mainly secreted by peripheral blood mononuclear cells; it competes with lipopolysaccharide for the binding to Toll-like receptor 4 and is involved in the inflammation12. Activation of resistin in the pancreatic islet cells inhibits insulin signaling via suppression of cell surface glucose transporters and a pro-inflammatory mechanism that results in β-cell loss, thus, a pro-diabetic effect5. Oddly the gradual increase in resistin levels (ng/mL), though not ascribed any statistically marked variation, was appreciable in both normoglycemic and preDM MetS groups vs. controls33.
SIRT 1 (sirtuin 1) is a protein from the sirtuin family of nicotinamide adenine dinucleotide-dependent deacylases (SIRT1-7) that are thought to be responsible mainly for the cardiometabolic benefits of lean diets and exercise, delaying key aspects of aging, e.g., decline in vascular endothelial function, metabolic syndrome, ischemia-reperfusion injury, obesity, and cardiomyopathy. Sirtuin activity steadily decreases with increasing age, and the decline is further exacerbated by obesity and sedentary lifestyles34. It was recently found that the defect in endothelial sirtuin 1 deacetylase activity is associated with (a) elevated basal and stimulated levels of superoxide generation (via the FoxO1 over-acetylation mechanism) and (b) increased nuclear translocation of NF-kB (via p65 over-acetylation mechanism). Based on these findings, the novel function of sirtuin 1 was proposed, namely, the maintenance of endothelial glycocalyx, particularly manifest in conditions associated with sirtuin 1 depletion35. It was found of reduced levels in MetS patients36. Visfatin is a highly conserved, 52 kDa protein expressed in a variety of tissues and cell types, including adipocytes, being much more abundant in visceral fat than in subcutaneous fat12. Visfatin has the dual effects as an adipocytokine, namely, as a global insulin-imitator and local adipogenic37. It has nicotinamide phosphoribosyltransferase (NAMPT) activity and, hence, an insulin-mimicking/insulin-sensitizing effects5. It binds to insulin receptor at a different site from that of insulin and stimulates glucose uptake in adipocytes and muscle cells and suppresses glucose release from hepatocytes12. The ZBED3 (zinc finger, BED-type (ZBED) protein 3) gene family comprises a closely related group of genes that contribute to the regulation of various functions by encoding regulatory proteins38. It was suggested that both Zbed3 and Axin2 have important roles in regulating Wnt activity while Wnt/b-catenin signaling has been shown to regulate adipogenesis and, thus, has a relationship with obesity and insulin resistance39.
Study design The study was approved by the Jordan University Hospital (JUH) Institutional Review Board (IRB). All procedures performed in the study were in accordance with the ethical standards of the IRB and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The potential study participants were approached randomly during their visits to the Family Medicine Clinic at the Jordan University Hospital (JUH). The participants were interviewed and their medical files were reviewed in order to assess the inclusion and exclusion criteria and in order to distribute them into the study groups. All potential candidates were informed thoroughly about the study; participants who agreed to take part in the study were asked to sign an informed consent form in Arabic. Data collection of patients’ medical histories was conducted until May 2020. All study participants were coded according to the study arm.
Study population This is a cross sectional study aimed to examine the relation between plasma levels of eighteen metabolic risk biomarkers (arranged alphabetically): Lipocalin, Nesfatin, Omentin,, Oxytocin, RBP-4 (retinol-binding protein-4), Resistin, SIRT 1 (sirtuin 1), Visfatin and ZBED3 (zinc finger, BED-type (ZBED) protein 3) in two groups of adult (18–75 years) Jordanian patients, namely, 1) Metabolic syndrome (MetS) group that included 61 individuals who were overweight or obese (BMI > 25 kg/m2) with 3 or more of MetS criteria40. According to the new IDF definition, for a person to be defined as having the MetS, they must have central obesity (defined as waist circumference with ethnicity specific values)* plus any two of four additional factors. These four factors are shown in Table 1.
Within the MetS group, any of the following individuals were included (Fig. 1):
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Control group that included 31 healthy individuals who were normoglycemic (a fasting plasma glucose (FPG) < 100 mg/dL or a hemoglobin A1c (A1C) < 5.7% 33)) and lean (BMI < 25 kg/m2)
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Prediabetes - a FPG of 100–125 mg/dL, or a 2-hour plasma glucose level of 140 mg/dL–199 mg/dL during a 75-g oral glucose tolerance test (OGTT), or A1C of 5.7–6.4%;
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Type 2 diabetes mellitus - a FPG level of ≥ 126 mg/dL, or OGTT, or random plasma glucose of 200 mg/dL or higher in a patient with classic symptoms of hyperglycemia or hyperglycemic crisis, or HbA1c level of 6.5% or higher41.
The following were exclusion criteria:
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Non-fasting individuals
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Pregnant or breast feeding/lactating women.
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Any prior use of anti-diabetic agent such as (sulfonylureas, meglitinides, biguanides, thiazolidinediones, alpha-glucosidase inhibitors, or insulin) either for diabetes itself or for any other condition.
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Any prior use of lipid lowering agents.
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Clinical evidence of autoimmune, life-threatening diseases, alcohol, drug abuse, and recently diagnosed and untreated endocrine disorder other than prediabetes or diabetes mellitus.
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Individuals with known inflammatory diseases such as the inflammatory bowel disease.
Anthropometric measurements Weight and height were measured using a balance mounted stadiometer. Waist circumference (WC) was measured using a nonstretchable tape at the midpoint between the last rib and the upper iliac crest, and hip circumference (HC) was measured around the widest section of the buttocks. Body mass index (BMI) was calculated as body weight (kg) divided by the square of height (m2). WHR and WHtR were calculated by dividing the WC (cm) by HC (cm) and height, respectively. Systolic blood pressure (SBP) and diastolic blood (DBP) pressures were measured using an electronic sphygmomanometer. Adiposity and atherogenecity indices were calculated using formulae42–44. Analysis of HbA1c, FPG and lipid profile were conducted,
Study design This cross sectional study meant to compare plasma and saliva levels of cardiometabolic risk factors in Control group of 30 participants who were apparently healthy, lean (BMI < 25 Kg/m2), and normoglycemic (HbA1c < 5.7%, FBS < 100 mg/dL), and two groups of overweight (BMI > 25 kg/m2) or obese (BMI > 30 kg/m2) drug-naïve MetS subjects, as defined by Alberti et al.45 The cases group included 29 normoglycemic MetS and 29 pre-diabetes MetS (Fig. 1). Individuals with any of the following assessed candidates with these criteria were excluded from the study: 16, 33, 36,45
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Non fasting individuals
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Any woman who is pregnant or breast feeding.
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Clinical evidence of autoimmune or life threatening disease (alcohol/drug abuse/recently diagnosed and untreated an endocrine disorder.
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Individuals with known inflammatory diseases such as the bowel inflammatory disease.
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Obesity secondary to endocrine derangement other than DM.
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Any prior treatment with any kind of antidiabetic medications used for diabetes or any other medical condition.
Clinical settings and duration The study was conducted at the Family Medicine Clinic and the General Laboratories of the Jordan University Hospital (JUH) in accordance with the Declaration of Helsinki. The project was approved by the IRB (Institutional Review Board (IRB) Bioethics Committee of the Jordan University Hospital (JUH) and the Scientific Research Committee at the School of Pharmacy, the University of Jordan. The eligible participants were informed in detail about the study and gave their written consent in Arabic. Participation in the study was voluntary. Furthermore, they were interviewed about their medical and family history alongside with reviewing their medical file to collect clinical information and laboratory data. Patient recruitment started at the beginning of July 2017 and ended by the beginning of December 2017.The anthropometric data such as height, waist circumference, blood pressure, and BMI were measured using specific tools. A venous blood was drawn from each candidate after 12 hours fasting to assess the levels of fasting plasma glucose (FPG) and lipid profile. The biochemical analysis of fasting lipid profile (HDL-C, LDL-C, TG, and TC), FPG, and HbA1c were performed for each participant. Table 2 displays the indices that were used in this study. Lipocalin 2, oxytocin, and nesfatin were procured from Abcam (Cambridge, MA, USA). Omentin, RBP-4 (retinol-binding protein-4), Resistin, SIRT 1 (sirtuin 1), Visfatin and ZBED3 (zinc finger, BED-type (ZBED) protein 3) were obtained from MyBiosourse, Inc. (San Diego, CA, USA). Markers’ plasma and salivary levels were assayed according to manufacturers’ instructions with intra- and interassay precisions of < 10-<12%. Harvested plasma (from lithium heparin collection tubes centrifuged at 4000 rpm for 10 minutes) were immediately stocked at -80oC until analysis. All saliva samples were collected via passive drool method into SalivaBio Saliva Collection Device (Salimetrics, Carlsbad, CA, USA). Immediately after collection, saliva samples were centrifuged for 15 min at 4000 rpm to remove any particles or sediments and supernatants using 2ml cryovials were stored at − 70 ◦C until analysis.
Statistical analysis Data were entered and analyzed via IBM SPSS© statistics 22 (SPSS, Inc., USA). Shapiro-Wilk test for was used for the assessment of normality of data distribution. Categorical data were expressed as numbers (%), normally distributed continuous data were expressed as mean (SD), and not normally distributed continuous data were expressed as median [interquartile range]. Gender differences between the study groups were tested using Chi-square test. While comparing continuous independent variables between the study groups we used the independent sample t-test for normally distributed data and Mann-Whitney test for data that were not normally distributed. Spearman correlation test was used for the assessment of correlations between plasma and salivary metabolic risk biomarkers as well as of selected biomarkers and clinical and laboratory parameters in both the total study sample and the MetS patients alone. Correlations were considered very strong, if correlation coefficient was at least 0.8; moderately strong, if the coefficient was 0.6 up to 0.8; fair, if the coefficient was 0.3 to 0.5 and poor if the coefficient was less than 0.346. For all statistical tests, p < 0.05 was determined as statistically significant.