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Volume 17, Issue 2 (2025)
3 2025, 17(2): 157-168 |
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Received: 2025/03/2 | Accepted: 2025/06/5 | Published: 2025/06/11
Received: 2025/03/2 | Accepted: 2025/06/5 | Published: 2025/06/11
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Abbas R, Alsaadi J. Clinical Changes in Adiponectin, Leptin, and Some Inflammatory Parameters in Obese Patients with Type 2 Diabetes and Hypertension. 3 2025; 17 (2) :157-168
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1- Department of Chemistry, Faculty of Science, University of Thi-Qar, Thi-Qar, Iraq
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Introduction
Obesity is defined as the excessive accumulation of fat in various parts of the body or in organs, referred to as ectopic fat, or throughout the body. It is a chronic, progressive, relapsing condition influenced by multiple factors that lead to adverse metabolic and psychosocial health consequences [1]. One of the primary causes of obesity is the imbalance between excess energy stored and energy utilized by the body, which can disrupt nutrient signals and result in insufficient energy expenditure. The diagnosis of obesity relies on the body mass index (BMI) cutoff, as well as the relationship between body weight, fat distribution patterns, and visceral fat [1, 2].
The pathophysiological mechanisms linking obesity and diabetes mellitus (DM) include alterations in β-cell function and insulin resistance in multiple organs. A significant mechanism is the increase in visceral fat, which results from the transportation of excess hepatic triglycerides (TGs) in very-low-density lipoproteins (vLDL) to various tissues, including the pancreatic β-cells, ultimately leading to β-cell dysfunction and type 2 diabetes mellitus (T2DM) [3]. Excess body fat, particularly intra-abdominal fat, is responsible for numerous metabolic abnormalities, such as increased plasma TGs, low HDL-cholesterol, and β-cell dysfunction. The increase in both basal and postprandial plasma insulin levels in obese individuals is due to heightened pancreatic insulin secretion and decreased clearance of peripheral plasma insulin [4]. In obesity, contributors to chronic inflammation include endoplasmic reticulum (ER) stress, decreased adiponectin (ADP) levels, increased leptin levels, macrophage infiltration, and lipolysis [5]. Furthermore, the ectopic accumulation of fat in muscles and adipose tissue in obese individuals leads to mitochondrial dysfunction and impaired mitochondrial oxidative activity and ATP synthesis. Obesity also accelerates the aging of adipose tissue and increases reactive oxygen species (ROS) formation in adipocytes, resulting in impaired glucose tolerance and insulin resistance (IR). Lastly, impaired translocation of glucose transporter type 4 (GLUT4) has been implicated in the development of IR within the obese population [6]. The risk of developing cardiovascular diseases (CVDs) is significantly higher in hypertensive obese individuals compared to their non-obese counterparts; it has been identified that 85% of high blood pressure occurs in patients with a BMI greater than 25 kg/m² [7, 8].
The relationship between obesity and hypertension (HTN) is complex and involves interactions among renal, metabolic, and neuroendocrine pathways. This relationship can be explained by several mechanisms, including enhanced renal absorption of sodium, stimulation of the renin-angiotensin-aldosterone system (RAAS), overactivation of the sympathetic nervous system (SNS), alterations in adipose-derived cytokines such as angiotensin (Ang) and leptin (LEP), and IR [7]. These factors manifest as increases in heart rate, elevated cardiac output, and renal tubular sodium reabsorption, which affect the kidneys and skeletal muscles [9, 10]. As a result, there is increased tubular sodium reabsorption and water retention, which consequently leads to HTN [11].
ADP is a 28-kDa protein hormone primarily secreted by lean adipocytes, playing a key role in the regulation of glucose and lipid metabolism. With a plasma concentration of 5-30 mg/L, it is the most abundant adipokine in human plasma [12]. Structurally, ADP is a 244-amino acid protein, and studies have underscored its unique role in activating various biochemical pathways that regulate metabolic functions [13, 14].
LEP, derived from the Greek word “leptos,” meaning thin, is a 16-kDa hormone protein synthesized primarily, although not exclusively, by white adipocytes [14]. Structurally, LEP consists of 167 amino acids derived from the human LEP gene [16] and plays a pivotal role in energy homeostasis, glucose metabolism, and body weight regulation [17]. It acts to suppress appetite through its direct effects on the hypothalamus. Plasma LEP concentration is directly related to fat mass and BMI [18]. Mechanisms contributing to LEP resistance include a reduction in the number of LEP receptors, impairment of receptor function, restricted tissue access, and molecular/cellular circulatory regulation [19, 20]. Several studies suggest that LEP deficiency poses a significant risk for obesity and CVDs. LEP resistance represents a complex and not fully understood pathophysiological phenomenon, highlighting the need for further investigation due to its clinical implications [15, 21].
C-reactive protein (CRP) is produced in response to pro-inflammatory cytokines, particularly interleukin-1 (IL-1), IL-6, and tumor necrosis factor-alpha (TNF-α). It is also produced by mature adipocytes and leukocytes in response to lipopolysaccharides. High concentrations of CRP can predict adverse vascular events and directly inhibit nitric oxide (NO) production. A prospective study showed that elevated levels of CRP impair endothelial regulation of vascular tone and are positively correlated with the risk of HTN [22, 23]. Additionally, CRP plays an important role in the pathophysiology of T2DM, with many cross-sectional studies concluding that chronic systemic inflammation, characterized by elevated levels of high-sensitivity CRP (Hs-CRP), may be a primary cause of IR in T2DM [24].
IL-6 is a pro-inflammatory cytokine produced by various cell types, including adipocytes, endothelial cells, pancreatic β-cells, macrophages, monocytes, and myeloid cells [25]. IL-6 binds to the membrane-bound IL-6 receptor, which is present in several cells, including endothelial cells and leukocytes, to activate its classical signaling cascade [26]. The actions of IL-6 contribute to lipid metabolism and the enhancement of insulin sensitivity in muscles [27], as well as appetite suppression. Other functions of IL-6 include coordinating the body’s immune response to infection, injury, or inflammation to induce and regulate the different elements of the acute-phase response. It also participates in the regulation of neural differentiation, maturation, function, and energy homeostasis [28].
The relationship between obesity and inflammation could also be mediated by hypoxia. Hypoxia is defined as a state of low oxygen availability that occurs in various physiological and pathological conditions [29]. On a cellular level, tissue adaptation to hypoxia is largely controlled by the hypoxia-inducible factor (HIF) signaling pathway. Which leads to drives levels of HIF-1α, a major transcription factor that regulates the cellular response to decreased oxygen availability through the expression of hundreds of hypoxia-dependent genes [30]. In obesity and CVDs, an up-regulation of the HIF pathway and an increased expression of hypoxic and angiogenic markers were observed [31], and the transcription factor HIF-1α is upregulated in the adipose tissue [32].
Based on this background, our study was designed to provide further insight into the relationship between cardiometabolic risks (BMI, blood pressure, blood glucose, etc.) and ADP, LEP, inflammatory factors, and HIF-1α levels in obese adults. This may help in understanding their contribution to the pathogenesis of obesity-induced DM and HTN.
Materials and Methods
Exclusion criteria
Design
This clinical follow-up study was conducted at Al-Nasiriya Teaching Hospital in Thi-Qar Governorate and the biochemistry laboratory at the College of Science from August 2024 to January 2025.
Sample
A total of 140 subjects (both male and female) were included, comprising 105 patients diagnosed with obesity (BMI≥30) and 35 control subjects with a BMI<5. The sample size was determined based on eligible patients available from August 2024 to January 2025. The participants’ ages ranged from 35 to 65 years. They were divided into four groups, including the control group, which included 35 healthy individuals, the obese group, consisting of 35 solely obese patients, the obese diabetes mellitus group, which included 35 obese patients with diabetes, and the obese hypertensive group, comprising 35 obese patients with hypertension. The sample size was determined based on eligible patients available from August 2024 to January 2025.
Inclusion and exclusion criteria
A convenience sample of 140 individuals was included in this study, comprising 105 individuals classified as obese and 35 individuals with a normal BMI, with an age range of 35 to 65 years. All individuals underwent the same clinical examinations and biochemical tests. The obese patients were recruited from the hospital advisory unit, while the control group consisted of relatives, friends, medical staff, and relatives of the patients. We obtained verbal consent from all individuals participating in this study in both groups. The study excluded any participants taking drugs that cause obesity or an increase in body weight, such as steroids and chemotherapy, as well as pregnant women. Additionally, smokers and patients with other chronic diseases, such as kidney disease, liver failure, thyroid disease, and immunological diseases, were also excluded.
Blood samples
About 5 ml of blood samples were collected from healthy subjects and patients in the morning, and the samples were divided into two parts. One part was collected in EDTA tubes, while the other part was collected in gel tubes. The gel tubes were left for half an hour and then centrifuged at 3000 rpm for 15 minutes. The serum samples were separated and stored at -20°C for later measurement of biochemical parameters, unless used immediately. The Adiponectin, HIF-1α, hs-CRP, IL-6, and Leptin ELISA kits were all supplied by SUNLONG, China, and utilized the enzymatic colorimetric method. Each piece of equipment and instrument was purchased from the following companies: the ELISA system (reader, washer, and printer) from Biotek in the USA, gel tubes from Jiangsu Xinkang in China, a micropipette from Slamed in Germany, and an ordinary centrifuge from Hettich in Germany.
Statistical analysis
All statistical analyses were performed using SPSS 26. All statistical analyses were performed using SPSS 26 at a significance level of p<0.05 and Microsoft Excel 2010. The results were expressed as mean±standard deviations and least significant difference (LSD). One-way analysis of variance (ANOVA) was used to compare parameters across the different studied groups. The Pearson correlation coefficient was used to measure the strength of a linear association between two parameters and also to test the relationships among the different parameters in each group.
Findings
The study included a total of 140 subjects (both male and female), among whom 105 were diagnosed with obesity (BMI≥30). Of these patients, 37 (35.24%) were male and 68 (64.76%) were female. Additionally, there were 35 control subjects (20 male and 15 female) with a BMI<25, with the duration of disease ranging from 5 to 15 years, and their ages were between 35 and 65 years (Table 1).
Table 1. Descriptive data for all studied groups
Serum adiponectin levels
There was a significant decrease in ADP levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in ADP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05). Although there was a difference in ADP levels among the patient groups (p<0.05), it was not significant (Table 2).
Table 2. Mean serum Adiponectin (ADP) levels in the studied groups
Serum leptin levels
There was a significant increase in LEP levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in LEP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05; Table 3).
Table 3. Mean serum Leptin (LEP) levels in the studied groups
Inflammatory markers
High-sensitivity C-reactive protein (hs-CRP)
There was a significant increase in hs-CRP levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in hs-CRP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05; Table 4).
Table 4. Mean serum high-sensitivity C-reactive protein (hs-CRP) levels in the studied groups
Interleukin-6
Regarding IL-6 levels, the current study found a significant increase in IL-6 levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in IL-6 levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05; Table 5).
Table 5. Mean serum interleukin-6 (IL-6) levels in the studied groups
Hypoxia inducible factor 1-α
There was no significant difference (p>0.05) in HIF-1α levels among all patient groups when compared to the control group (Table 6). While there was a difference in HIF-1α concentration between the groups (p>0.05), it was not statistically significant.
Table 6. Mean serum HIF-1α levels in the studied groups
Relationship between leptin and adiponectin levels
There was no significant positive correlation between LEP and ADP levels in each of the obese group (r=0.061), the obese hypertension group (r=-0.067), and the obese diabetes mellitus group (r=-0.118; Figure 1).
Figure 1. Correlation between ADP and LEP levels in the groups
There was no significant positive correlation between ADP levels and BMI in each of the obese group (r=0.099), the obese hypertension group (r=0.136), and the obese diabetes mellitus group (r=0.317; Figure 2).
Figure 2. Correlation between ADP and BMI in patient groups
Additionally, there was no significant positive correlation between LEP levels and BMI in each of the obese group (r=0.060), the obese hypertension group (r=-0.013), and the obese diabetes mellitus group (r=0.122; Figure 3).
Figure 3. Correlation between LEP levels and BMI in patient groups
There was no significant negative correlation between ADP and IL-6 levels in each of the obese group (r=0.068), the obese hypertension group (r=-0.042), and the obese diabetes mellitus group (r=-0.068; Figure 4).
Figure 4. Correlation between ADP and IL-6 levels in patient groups
In contrast, there was a significant, strong positive correlation between LEP and IL-6 levels in each of the obese group (r=0.644), the obese hypertension group (r=0.842), and the obese diabetes mellitus group (r=0.869; Figure 5).
Figure 5. Correlation between LEP and IL-6 levels in patient groups
There was no significant correlation between ADP and hs-CRP levels in each of the obese group (r=0.028), the obese hypertension group (r=0.107), and the obese diabetes mellitus group (r=-0.263; Figure 6).
Figure 6. Correlation between ADP and hs-CRP levels in patient groups
Additionally, there was no significant negative correlation between LEP and hs-CRP levels in each of the obese group (r=-0.138) and the obese hypertension group (r=-0.194), while there was a significant positive correlation in the obese diabetes mellitus group (r=0.336; Figure 7).
Figure 7. Correlation between LEP and hs-CRP levels in patient groups
There was no significant negative correlation between ADP and HIF 1-alpha levels in each of the obese group (r=-0.175), the obese hypertension group (r=0.135), and the obese diabetes mellitus group (r=-0.164; Figure 8).
Figure 8. Correlation between ADP and HIF-1α levels in patient groups
Lastly, there was no significant negative correlation between LEP and HIF-1α levels in each of the obese group (r=-0.235), the obese hypertension group (r=0.054), and the obese diabetes mellitus group (r=-0.001; Figure 9).
Figure 9. Correlation between LEP and HIF-1α levels in patient groups
Discussion
The current study aimed to investigate changes in ADP, leptin, and some inflammatory factors in the serum of obese patients with T2DM and HTN in Thi-Qar Province, Iraq. There was a significant decrease in ADP levels in all patient groups compared to the control group. Our results are also consistent with the study by Liu et al. [33]. ADP has been recognized as a metabolically favorable adipocytokine. Previous studies have shown that ADP has many metabolic effects, particularly in regulating lipid metabolism, enhancing insulin sensitivity, and exhibiting anti-inflammatory properties by regulating glucose levels and fatty acid breakdown. These functions may play potential roles linked to ADP in protecting against obesity-related diseases [34, 35]. Although ADP is primarily secreted by adipose tissue, its circulating concentration decreases in obesity, as noted by Baldelli et al. [36]. This finding is consistent with our results, as the serum ADP levels in the control group were significantly higher than those in the obese group. This result also aligns with the findings of the study by Wu et al. [37].
The decrease in serum ADP levels in obese individuals may be attributed to fat cell dysfunction and/or hypermethylation of the ADP gene in cases of morbid obesity [38]. Previous studies have revealed that the quality of adipose tissue is largely compromised in patients with CVD [39, 40]. Other studies have shown that serum ADP levels are negatively correlated with the visceral adiposity index (VAI). VAI is a mathematical formula that estimates the amount and function of visceral adipose tissue (VAT), which is the fat that surrounds the internal organs in the abdomen [41, 42]. Generally, VAT is associated with lower ADP levels and a higher risk for metabolic and cardiovascular complications such as diabetes mellitus, HTN, and atherosclerosis. This association arises because VAT is more prone to inflammation, IR, and lipolysis, which can impair ADP secretion and action [43]. Moreover, cumulative clinical evidence indicates that ADP levels are negatively correlated with IR, T2DM, and metabolic syndrome in human subjects [44, 45]. Clinical experiments and longitudinal studies have reported inconsistent results regarding the antihypertensive effects of ADP [46, 47]. According to the vast majority of reports, ADP has been shown to have a protective effect on vascular functions, resulting in a negative relationship with blood pressure and a reduction in the incidence of obesity-related HTN [48, 49]. The results of this research suggest that ADP may not always have a strong direct relationship with HTN and DM. The significance of ADP must be viewed within the context of the body’s key signaling pathways that regulate metabolic equilibrium in the presence of obesity and cardiovascular disorders [50].
There was a significant increase in LEP levels in all patient groups compared to the control group. However, there was no significant difference in LEP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group.
According to a study by Bhat et al., participants who are obese or have obesity-related HTN exhibit considerably higher LEP levels than those who are neither obese nor have normotension. This outcome is consistent with our research [51]. A considerable number of studies have observed a strong correlation between LEP and both HTN and DM in animals and humans, implicating LEP as having a significant role in the pathophysiology of obesity-induced DM and HTN [52, 53]. Our study revealed that serum LEP levels were significantly higher in obese patients, which aligns with the fact that LEP is related to the degree of body adiposity. According to Guarino et al., serum LEP rises with obesity, and BMI is the most important factor associated with elevated blood LEP levels, as indicated by many investigations [54, 55], which supports our findings. In another study, BMI, body fat mass, and blood LEP levels are also found to be strongly correlated. Subcutaneous abdominal adipocytes secrete three times more LEP than intra-abdominal fat. Subcutaneous adipocytes are the principal source of serum LEP [56], which partly explains the elevated LEP levels observed in our participants.
Numerous studies have demonstrated a strong correlation between LEP levels and body fat percentage, with an increase in adipocytes triggering elevated LEP as an adaptive response for energy balance control [57, 58]. Patients with obesity have been observed to experience increased appetite and hyperphagia even with elevated LEP levels, suggesting the possibility of LEP resistance. This resistance may contribute to increased calorie intake and hinder weight loss [59]. It arises from obesity-related processes that impair LEP function; this impairment can result from reduced expression of LEP receptors (LepR), altered signaling pathways, or disruptions in LEP transport across the blood-brain barrier (BBB) [60, 61]. Ultimately, these factors contribute to the progression of obesity. Despite elevated LEP levels, hypothalamic neurons may become less sensitive to LEP or fail to respond appropriately [15]. Thus, LEP loses its physiological functions and acquires pathological ones [62].
There was a close relationship between LEP levels and body adiposity; however, whether these high LEP levels independently contribute to high blood pressure is not known [53]. Our study revealed a direct and positive significant relationship between plasma LEP and BMI. However, there was no difference in LEP levels between the obese HTN group and the obese group. Therefore, there was no evidence for an independent contribution of LEP to blood pressure; thus, BMI was the factor that largely explained the association between LEP and blood pressure. The response associated with LEP-induced susceptibility to obesity-related HTN may be explained by genotypic differences in humans [63]. Additionally, previous reports indicated that there is no difference in LEP concentrations between T2DM patients and healthy controls, who did not differ from each other in age, BMI, and waist circumference [64, 65].
There was a significant increase in hs-CRP levels in all patient groups compared to the controls. However, there was no significant difference in hs-CRP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group. Our results study aligns with a study by Uludağ et al., which noted that hs-CRP levels increase with increasing BMI among overweight and morbidly obese participants compared to the normal group [66]. Our results are also consistent with the study by Marfianti & Andriyan, reporting a significant correlation between BMI and serum hs-CRP levels in overweight and obese individuals [67]. This finding is further supported by a case-control study by Mulyamin et al., stating that BMI is a factor affecting hs-CRP levels in overweight and obese individuals, regardless of whether they have T2DM [68]. According to Rattu et al., there is a significant positive relationship between BMI and hs-CRP levels in obese students, while there is no significant relationship between BMI and hs-CRP levels in non-obese students [69]. The increase in both BMI and hs-CRP can become a risk factor for the development of atherosclerosis and subsequent heart disease [70].
Based on our results, we can conclude that obesity is the primary influence on hs-CRP levels, as obesity is a chronic inflammatory condition. The hypothesis explaining the relationship between markers of inflammatory response and IR suggests that chronic inflammation can act as an inducer of IR or stimulate hs-CRP synthesis, ultimately leading to T2DM [71]. A previous study has indicated an association between hs-CRP and an increased risk of DM and metabolic syndrome [72]. According to a study by Mesa et al., hs-CRP is correlated with BMI, BP, TGs, HDL cholesterol, fasting blood glucose, and other risk factors, thereby increasing the risk of metabolic syndrome [73]. In a study of 1,630 Chinese adults, Shen et al. found that overweight/obesity is an independent predictor of hs-CRP elevation, even after considering several traditional confounding factors. Additionally, the increase in hs-CRP levels is found to be a predictor of a higher risk of cardiovascular events and cardiovascular mortality in the future [74]. Furthermore, another cross-sectional study reported that the risk of elevated hs-CRP in overweight and obese groups is 1.2 and 1.7 times greater than in the normal weight group, respectively [75].
Obesity induces adipocyte dysfunction, with adipokine secretion and macrophage activation leading to pro-inflammatory cytokines such as TNF-α and IL-6, which are associated with elevated circulating hs-CRP levels [73]. These changes in the release of adipocytokines induce a state of systemic IR and low-grade inflammation. Similarly, Makki et al. demonstrated that elevated hs-CRP levels were related to increased abdominal fat [76]. Additionally, previous research has shown that diet-induced weight reduction is associated with reduced blood levels of IL-6, TNF-α, and hs-CRP [77]. Our findings support the view that obesity is responsible for a low degree of systemic inflammation. Therefore, controlling body weight is important to reduce the risk of hs-CRP-related diseases in the future.
Regarding IL-6 levels, the current study found a significant increase in IL-6 levels in all patient groups compared to the control group. However, there was no significant difference in IL-6 levels between the obese diabetes group and the obese hypertensive group when compared with the obese group. Obesity is a significant characteristic of metabolic syndrome, and the association between the two has been attributed to a chronic inflammatory process [78]. IL-6 is an important mediator of acute-phase reactions, and its levels are correlated with CRP levels [79]. As a result, both IL-6 and CRP are used clinically as biomarkers of inflammation. The present results are consistent with a study by Ismail et al. [80], noting statistically significantly higher IL-6 levels in the obese groups compared to the normal group. There was a statistically significant positive correlation between serum IL-6 and BMI. This finding is also consistent with El-Mikkawy et al.'s study, discovering that very significantly elevated circulating concentrations of IL-6 are observed in patients who were overweight or obese, regardless of whether they had chronic diseases [81]. Baikpour et al. found that IR is correlated with plasma levels of IL-6 in individuals with abdominal obesity; a strong positive correlation is also observed between serum IL-6 levels and BMI in healthy participants with obesity. According to Baikpour et al., IL-6 expression is greater in the adipose tissue of obese individuals than in that of non-obese individuals [82]. Hypothalamic upregulation of IL-6 receptor expression suggests that IL-6 may play a role in regulating energy intake and appetite [83].
Macrophages are the predominant immune cell population in human adipose tissue, constituting approximately 10% of the cellular composition of AT. The development of obesity is intricately linked with adipocyte hypertrophy, which triggers an inflammatory cascade that increases the number of adipose tissue macrophages (ATMs) [84] and alters their inflammatory profile. Obesity induces a shift in the distribution of T-cell subtypes, characterized by a decrease in anti-inflammatory regulatory T cells (Tregs) and T-helper (Th2) cells, alongside an increase in pro-inflammatory Th1 and Th17 cells. Consequently, an abundance of these pro-inflammatory T-cell subtypes is associated with elevated expression of IL-6 [85]. Finally, obesity and non-cardiovascular inflammatory diseases significantly influence serum IL-6 levels. The authors do not reach a consensus regarding IL-6’s potential as a biomarker for the onset of HTN and DM in healthy individuals.
Unexpectedly, we did not observe any differences in HIF-1α levels in obese patients, possibly due to population characteristics, such as age and sex. It may also be because physiological conditions are insufficient to stimulate HIF-1α, especially in chronic, subacute cases, as there may not be enough oxygen to clearly stimulate HIF-1α gene expression. Additionally, the effect of drug therapy may play a role; drugs used to treat diabetes and high blood pressure may affect the expression of HIF-1α. For example, several studies have shown that metformin (a common diabetes drug) can modify the response of HIF-1α in endothelial cells, thereby increasing its expression by reprogramming oxygen consumption in mitochondria, which leads to increased intracellular oxygen availability and enhances the degradation of HIF-1α [86, 87]. Several studies have also indicated that antihypertensive drugs (especially angiotensin antagonists, like ACE inhibitors and ARBs) can affect the gene expression of HIF-1α [88, 89]. The stage of the disease may also influence HIF-1α levels. In the early stages of chronic diseases, such as diabetes and HTN, HIF-1α may not be evident. A study showed that HIF-1α expression may be lower in disease states, especially in the early stages [90]. Ultimately, this result may be attributed to individual differences and biological variation. There may be individual variation among study participants in terms of genetics, lifestyle, or disease severity, which accounts for the differences between groups [91].
The main limitation of this study is the small sample size of the obese, hypertensive, type 2 diabetes, and control groups. Furthermore, this study was restricted to only one province. As a next step, we plan to expand the sample size and conduct research in multiple provinces. Additionally, future well-designed, gender-specific studies are needed to evaluate the role of hormones and inflammatory factors in the development of obesity-related complications.
Conclusion
Obese patients with type 2 diabetes and hypertension exhibit significantly higher levels of LEP and inflammatory factors and significantly lower levels of ADP compared to the control group.
Acknowledgments: The authors sincerely thank my family for their endless support and encouragement.
Ethical Permissions: Approvals from the scientific committee in the Chemistry Department, College of Sciences, University of Thi-Qar, as well as from the Thi-Qar Health Department, Training and Human Development Center, and Research Committee of the current study, were obtained. Oral consent for the study procedure was received from all participants enrolled in the study.
Conflicts of Interests: The authors declared no conflicts of interests.
Authors' Contribution: Abbas RK (First Author), Introduction Writer/Methodologist/Main Researcher/Discussion Writer/Statistical Analyst (50%); Alsaadi JHH (Second Author), Introduction Writer/Methodologist/Assistant Researcher/Discussion Writer/Statistical Analyst (50%)
Funding/Support: This research was self-funded.
Obesity is defined as the excessive accumulation of fat in various parts of the body or in organs, referred to as ectopic fat, or throughout the body. It is a chronic, progressive, relapsing condition influenced by multiple factors that lead to adverse metabolic and psychosocial health consequences [1]. One of the primary causes of obesity is the imbalance between excess energy stored and energy utilized by the body, which can disrupt nutrient signals and result in insufficient energy expenditure. The diagnosis of obesity relies on the body mass index (BMI) cutoff, as well as the relationship between body weight, fat distribution patterns, and visceral fat [1, 2].
The pathophysiological mechanisms linking obesity and diabetes mellitus (DM) include alterations in β-cell function and insulin resistance in multiple organs. A significant mechanism is the increase in visceral fat, which results from the transportation of excess hepatic triglycerides (TGs) in very-low-density lipoproteins (vLDL) to various tissues, including the pancreatic β-cells, ultimately leading to β-cell dysfunction and type 2 diabetes mellitus (T2DM) [3]. Excess body fat, particularly intra-abdominal fat, is responsible for numerous metabolic abnormalities, such as increased plasma TGs, low HDL-cholesterol, and β-cell dysfunction. The increase in both basal and postprandial plasma insulin levels in obese individuals is due to heightened pancreatic insulin secretion and decreased clearance of peripheral plasma insulin [4]. In obesity, contributors to chronic inflammation include endoplasmic reticulum (ER) stress, decreased adiponectin (ADP) levels, increased leptin levels, macrophage infiltration, and lipolysis [5]. Furthermore, the ectopic accumulation of fat in muscles and adipose tissue in obese individuals leads to mitochondrial dysfunction and impaired mitochondrial oxidative activity and ATP synthesis. Obesity also accelerates the aging of adipose tissue and increases reactive oxygen species (ROS) formation in adipocytes, resulting in impaired glucose tolerance and insulin resistance (IR). Lastly, impaired translocation of glucose transporter type 4 (GLUT4) has been implicated in the development of IR within the obese population [6]. The risk of developing cardiovascular diseases (CVDs) is significantly higher in hypertensive obese individuals compared to their non-obese counterparts; it has been identified that 85% of high blood pressure occurs in patients with a BMI greater than 25 kg/m² [7, 8].
The relationship between obesity and hypertension (HTN) is complex and involves interactions among renal, metabolic, and neuroendocrine pathways. This relationship can be explained by several mechanisms, including enhanced renal absorption of sodium, stimulation of the renin-angiotensin-aldosterone system (RAAS), overactivation of the sympathetic nervous system (SNS), alterations in adipose-derived cytokines such as angiotensin (Ang) and leptin (LEP), and IR [7]. These factors manifest as increases in heart rate, elevated cardiac output, and renal tubular sodium reabsorption, which affect the kidneys and skeletal muscles [9, 10]. As a result, there is increased tubular sodium reabsorption and water retention, which consequently leads to HTN [11].
ADP is a 28-kDa protein hormone primarily secreted by lean adipocytes, playing a key role in the regulation of glucose and lipid metabolism. With a plasma concentration of 5-30 mg/L, it is the most abundant adipokine in human plasma [12]. Structurally, ADP is a 244-amino acid protein, and studies have underscored its unique role in activating various biochemical pathways that regulate metabolic functions [13, 14].
LEP, derived from the Greek word “leptos,” meaning thin, is a 16-kDa hormone protein synthesized primarily, although not exclusively, by white adipocytes [14]. Structurally, LEP consists of 167 amino acids derived from the human LEP gene [16] and plays a pivotal role in energy homeostasis, glucose metabolism, and body weight regulation [17]. It acts to suppress appetite through its direct effects on the hypothalamus. Plasma LEP concentration is directly related to fat mass and BMI [18]. Mechanisms contributing to LEP resistance include a reduction in the number of LEP receptors, impairment of receptor function, restricted tissue access, and molecular/cellular circulatory regulation [19, 20]. Several studies suggest that LEP deficiency poses a significant risk for obesity and CVDs. LEP resistance represents a complex and not fully understood pathophysiological phenomenon, highlighting the need for further investigation due to its clinical implications [15, 21].
C-reactive protein (CRP) is produced in response to pro-inflammatory cytokines, particularly interleukin-1 (IL-1), IL-6, and tumor necrosis factor-alpha (TNF-α). It is also produced by mature adipocytes and leukocytes in response to lipopolysaccharides. High concentrations of CRP can predict adverse vascular events and directly inhibit nitric oxide (NO) production. A prospective study showed that elevated levels of CRP impair endothelial regulation of vascular tone and are positively correlated with the risk of HTN [22, 23]. Additionally, CRP plays an important role in the pathophysiology of T2DM, with many cross-sectional studies concluding that chronic systemic inflammation, characterized by elevated levels of high-sensitivity CRP (Hs-CRP), may be a primary cause of IR in T2DM [24].
IL-6 is a pro-inflammatory cytokine produced by various cell types, including adipocytes, endothelial cells, pancreatic β-cells, macrophages, monocytes, and myeloid cells [25]. IL-6 binds to the membrane-bound IL-6 receptor, which is present in several cells, including endothelial cells and leukocytes, to activate its classical signaling cascade [26]. The actions of IL-6 contribute to lipid metabolism and the enhancement of insulin sensitivity in muscles [27], as well as appetite suppression. Other functions of IL-6 include coordinating the body’s immune response to infection, injury, or inflammation to induce and regulate the different elements of the acute-phase response. It also participates in the regulation of neural differentiation, maturation, function, and energy homeostasis [28].
The relationship between obesity and inflammation could also be mediated by hypoxia. Hypoxia is defined as a state of low oxygen availability that occurs in various physiological and pathological conditions [29]. On a cellular level, tissue adaptation to hypoxia is largely controlled by the hypoxia-inducible factor (HIF) signaling pathway. Which leads to drives levels of HIF-1α, a major transcription factor that regulates the cellular response to decreased oxygen availability through the expression of hundreds of hypoxia-dependent genes [30]. In obesity and CVDs, an up-regulation of the HIF pathway and an increased expression of hypoxic and angiogenic markers were observed [31], and the transcription factor HIF-1α is upregulated in the adipose tissue [32].
Based on this background, our study was designed to provide further insight into the relationship between cardiometabolic risks (BMI, blood pressure, blood glucose, etc.) and ADP, LEP, inflammatory factors, and HIF-1α levels in obese adults. This may help in understanding their contribution to the pathogenesis of obesity-induced DM and HTN.
Materials and Methods
Exclusion criteria
Design
This clinical follow-up study was conducted at Al-Nasiriya Teaching Hospital in Thi-Qar Governorate and the biochemistry laboratory at the College of Science from August 2024 to January 2025.
Sample
A total of 140 subjects (both male and female) were included, comprising 105 patients diagnosed with obesity (BMI≥30) and 35 control subjects with a BMI<5. The sample size was determined based on eligible patients available from August 2024 to January 2025. The participants’ ages ranged from 35 to 65 years. They were divided into four groups, including the control group, which included 35 healthy individuals, the obese group, consisting of 35 solely obese patients, the obese diabetes mellitus group, which included 35 obese patients with diabetes, and the obese hypertensive group, comprising 35 obese patients with hypertension. The sample size was determined based on eligible patients available from August 2024 to January 2025.
Inclusion and exclusion criteria
A convenience sample of 140 individuals was included in this study, comprising 105 individuals classified as obese and 35 individuals with a normal BMI, with an age range of 35 to 65 years. All individuals underwent the same clinical examinations and biochemical tests. The obese patients were recruited from the hospital advisory unit, while the control group consisted of relatives, friends, medical staff, and relatives of the patients. We obtained verbal consent from all individuals participating in this study in both groups. The study excluded any participants taking drugs that cause obesity or an increase in body weight, such as steroids and chemotherapy, as well as pregnant women. Additionally, smokers and patients with other chronic diseases, such as kidney disease, liver failure, thyroid disease, and immunological diseases, were also excluded.
Blood samples
About 5 ml of blood samples were collected from healthy subjects and patients in the morning, and the samples were divided into two parts. One part was collected in EDTA tubes, while the other part was collected in gel tubes. The gel tubes were left for half an hour and then centrifuged at 3000 rpm for 15 minutes. The serum samples were separated and stored at -20°C for later measurement of biochemical parameters, unless used immediately. The Adiponectin, HIF-1α, hs-CRP, IL-6, and Leptin ELISA kits were all supplied by SUNLONG, China, and utilized the enzymatic colorimetric method. Each piece of equipment and instrument was purchased from the following companies: the ELISA system (reader, washer, and printer) from Biotek in the USA, gel tubes from Jiangsu Xinkang in China, a micropipette from Slamed in Germany, and an ordinary centrifuge from Hettich in Germany.
Statistical analysis
All statistical analyses were performed using SPSS 26. All statistical analyses were performed using SPSS 26 at a significance level of p<0.05 and Microsoft Excel 2010. The results were expressed as mean±standard deviations and least significant difference (LSD). One-way analysis of variance (ANOVA) was used to compare parameters across the different studied groups. The Pearson correlation coefficient was used to measure the strength of a linear association between two parameters and also to test the relationships among the different parameters in each group.
Findings
The study included a total of 140 subjects (both male and female), among whom 105 were diagnosed with obesity (BMI≥30). Of these patients, 37 (35.24%) were male and 68 (64.76%) were female. Additionally, there were 35 control subjects (20 male and 15 female) with a BMI<25, with the duration of disease ranging from 5 to 15 years, and their ages were between 35 and 65 years (Table 1).
Table 1. Descriptive data for all studied groups
Serum adiponectin levels
There was a significant decrease in ADP levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in ADP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05). Although there was a difference in ADP levels among the patient groups (p<0.05), it was not significant (Table 2).
Table 2. Mean serum Adiponectin (ADP) levels in the studied groups
Serum leptin levels
There was a significant increase in LEP levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in LEP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05; Table 3).
Table 3. Mean serum Leptin (LEP) levels in the studied groups
Inflammatory markers
High-sensitivity C-reactive protein (hs-CRP)
There was a significant increase in hs-CRP levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in hs-CRP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05; Table 4).
Table 4. Mean serum high-sensitivity C-reactive protein (hs-CRP) levels in the studied groups
Interleukin-6
Regarding IL-6 levels, the current study found a significant increase in IL-6 levels in all patient groups compared to the control group (p≤0.05). However, there was no significant difference in IL-6 levels between the obese diabetes group and the obese hypertensive group when compared with the obese group (p≤0.05; Table 5).
Table 5. Mean serum interleukin-6 (IL-6) levels in the studied groups
Hypoxia inducible factor 1-α
There was no significant difference (p>0.05) in HIF-1α levels among all patient groups when compared to the control group (Table 6). While there was a difference in HIF-1α concentration between the groups (p>0.05), it was not statistically significant.
Table 6. Mean serum HIF-1α levels in the studied groups
Relationship between leptin and adiponectin levels
There was no significant positive correlation between LEP and ADP levels in each of the obese group (r=0.061), the obese hypertension group (r=-0.067), and the obese diabetes mellitus group (r=-0.118; Figure 1).
Figure 1. Correlation between ADP and LEP levels in the groups
There was no significant positive correlation between ADP levels and BMI in each of the obese group (r=0.099), the obese hypertension group (r=0.136), and the obese diabetes mellitus group (r=0.317; Figure 2).
Figure 2. Correlation between ADP and BMI in patient groups
Additionally, there was no significant positive correlation between LEP levels and BMI in each of the obese group (r=0.060), the obese hypertension group (r=-0.013), and the obese diabetes mellitus group (r=0.122; Figure 3).
Figure 3. Correlation between LEP levels and BMI in patient groups
There was no significant negative correlation between ADP and IL-6 levels in each of the obese group (r=0.068), the obese hypertension group (r=-0.042), and the obese diabetes mellitus group (r=-0.068; Figure 4).
Figure 4. Correlation between ADP and IL-6 levels in patient groups
In contrast, there was a significant, strong positive correlation between LEP and IL-6 levels in each of the obese group (r=0.644), the obese hypertension group (r=0.842), and the obese diabetes mellitus group (r=0.869; Figure 5).
Figure 5. Correlation between LEP and IL-6 levels in patient groups
There was no significant correlation between ADP and hs-CRP levels in each of the obese group (r=0.028), the obese hypertension group (r=0.107), and the obese diabetes mellitus group (r=-0.263; Figure 6).
Figure 6. Correlation between ADP and hs-CRP levels in patient groups
Additionally, there was no significant negative correlation between LEP and hs-CRP levels in each of the obese group (r=-0.138) and the obese hypertension group (r=-0.194), while there was a significant positive correlation in the obese diabetes mellitus group (r=0.336; Figure 7).
Figure 7. Correlation between LEP and hs-CRP levels in patient groups
There was no significant negative correlation between ADP and HIF 1-alpha levels in each of the obese group (r=-0.175), the obese hypertension group (r=0.135), and the obese diabetes mellitus group (r=-0.164; Figure 8).
Figure 8. Correlation between ADP and HIF-1α levels in patient groups
Lastly, there was no significant negative correlation between LEP and HIF-1α levels in each of the obese group (r=-0.235), the obese hypertension group (r=0.054), and the obese diabetes mellitus group (r=-0.001; Figure 9).
Figure 9. Correlation between LEP and HIF-1α levels in patient groups
Discussion
The current study aimed to investigate changes in ADP, leptin, and some inflammatory factors in the serum of obese patients with T2DM and HTN in Thi-Qar Province, Iraq. There was a significant decrease in ADP levels in all patient groups compared to the control group. Our results are also consistent with the study by Liu et al. [33]. ADP has been recognized as a metabolically favorable adipocytokine. Previous studies have shown that ADP has many metabolic effects, particularly in regulating lipid metabolism, enhancing insulin sensitivity, and exhibiting anti-inflammatory properties by regulating glucose levels and fatty acid breakdown. These functions may play potential roles linked to ADP in protecting against obesity-related diseases [34, 35]. Although ADP is primarily secreted by adipose tissue, its circulating concentration decreases in obesity, as noted by Baldelli et al. [36]. This finding is consistent with our results, as the serum ADP levels in the control group were significantly higher than those in the obese group. This result also aligns with the findings of the study by Wu et al. [37].
The decrease in serum ADP levels in obese individuals may be attributed to fat cell dysfunction and/or hypermethylation of the ADP gene in cases of morbid obesity [38]. Previous studies have revealed that the quality of adipose tissue is largely compromised in patients with CVD [39, 40]. Other studies have shown that serum ADP levels are negatively correlated with the visceral adiposity index (VAI). VAI is a mathematical formula that estimates the amount and function of visceral adipose tissue (VAT), which is the fat that surrounds the internal organs in the abdomen [41, 42]. Generally, VAT is associated with lower ADP levels and a higher risk for metabolic and cardiovascular complications such as diabetes mellitus, HTN, and atherosclerosis. This association arises because VAT is more prone to inflammation, IR, and lipolysis, which can impair ADP secretion and action [43]. Moreover, cumulative clinical evidence indicates that ADP levels are negatively correlated with IR, T2DM, and metabolic syndrome in human subjects [44, 45]. Clinical experiments and longitudinal studies have reported inconsistent results regarding the antihypertensive effects of ADP [46, 47]. According to the vast majority of reports, ADP has been shown to have a protective effect on vascular functions, resulting in a negative relationship with blood pressure and a reduction in the incidence of obesity-related HTN [48, 49]. The results of this research suggest that ADP may not always have a strong direct relationship with HTN and DM. The significance of ADP must be viewed within the context of the body’s key signaling pathways that regulate metabolic equilibrium in the presence of obesity and cardiovascular disorders [50].
There was a significant increase in LEP levels in all patient groups compared to the control group. However, there was no significant difference in LEP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group.
According to a study by Bhat et al., participants who are obese or have obesity-related HTN exhibit considerably higher LEP levels than those who are neither obese nor have normotension. This outcome is consistent with our research [51]. A considerable number of studies have observed a strong correlation between LEP and both HTN and DM in animals and humans, implicating LEP as having a significant role in the pathophysiology of obesity-induced DM and HTN [52, 53]. Our study revealed that serum LEP levels were significantly higher in obese patients, which aligns with the fact that LEP is related to the degree of body adiposity. According to Guarino et al., serum LEP rises with obesity, and BMI is the most important factor associated with elevated blood LEP levels, as indicated by many investigations [54, 55], which supports our findings. In another study, BMI, body fat mass, and blood LEP levels are also found to be strongly correlated. Subcutaneous abdominal adipocytes secrete three times more LEP than intra-abdominal fat. Subcutaneous adipocytes are the principal source of serum LEP [56], which partly explains the elevated LEP levels observed in our participants.
Numerous studies have demonstrated a strong correlation between LEP levels and body fat percentage, with an increase in adipocytes triggering elevated LEP as an adaptive response for energy balance control [57, 58]. Patients with obesity have been observed to experience increased appetite and hyperphagia even with elevated LEP levels, suggesting the possibility of LEP resistance. This resistance may contribute to increased calorie intake and hinder weight loss [59]. It arises from obesity-related processes that impair LEP function; this impairment can result from reduced expression of LEP receptors (LepR), altered signaling pathways, or disruptions in LEP transport across the blood-brain barrier (BBB) [60, 61]. Ultimately, these factors contribute to the progression of obesity. Despite elevated LEP levels, hypothalamic neurons may become less sensitive to LEP or fail to respond appropriately [15]. Thus, LEP loses its physiological functions and acquires pathological ones [62].
There was a close relationship between LEP levels and body adiposity; however, whether these high LEP levels independently contribute to high blood pressure is not known [53]. Our study revealed a direct and positive significant relationship between plasma LEP and BMI. However, there was no difference in LEP levels between the obese HTN group and the obese group. Therefore, there was no evidence for an independent contribution of LEP to blood pressure; thus, BMI was the factor that largely explained the association between LEP and blood pressure. The response associated with LEP-induced susceptibility to obesity-related HTN may be explained by genotypic differences in humans [63]. Additionally, previous reports indicated that there is no difference in LEP concentrations between T2DM patients and healthy controls, who did not differ from each other in age, BMI, and waist circumference [64, 65].
There was a significant increase in hs-CRP levels in all patient groups compared to the controls. However, there was no significant difference in hs-CRP levels between the obese diabetes group and the obese hypertensive group when compared with the obese group. Our results study aligns with a study by Uludağ et al., which noted that hs-CRP levels increase with increasing BMI among overweight and morbidly obese participants compared to the normal group [66]. Our results are also consistent with the study by Marfianti & Andriyan, reporting a significant correlation between BMI and serum hs-CRP levels in overweight and obese individuals [67]. This finding is further supported by a case-control study by Mulyamin et al., stating that BMI is a factor affecting hs-CRP levels in overweight and obese individuals, regardless of whether they have T2DM [68]. According to Rattu et al., there is a significant positive relationship between BMI and hs-CRP levels in obese students, while there is no significant relationship between BMI and hs-CRP levels in non-obese students [69]. The increase in both BMI and hs-CRP can become a risk factor for the development of atherosclerosis and subsequent heart disease [70].
Based on our results, we can conclude that obesity is the primary influence on hs-CRP levels, as obesity is a chronic inflammatory condition. The hypothesis explaining the relationship between markers of inflammatory response and IR suggests that chronic inflammation can act as an inducer of IR or stimulate hs-CRP synthesis, ultimately leading to T2DM [71]. A previous study has indicated an association between hs-CRP and an increased risk of DM and metabolic syndrome [72]. According to a study by Mesa et al., hs-CRP is correlated with BMI, BP, TGs, HDL cholesterol, fasting blood glucose, and other risk factors, thereby increasing the risk of metabolic syndrome [73]. In a study of 1,630 Chinese adults, Shen et al. found that overweight/obesity is an independent predictor of hs-CRP elevation, even after considering several traditional confounding factors. Additionally, the increase in hs-CRP levels is found to be a predictor of a higher risk of cardiovascular events and cardiovascular mortality in the future [74]. Furthermore, another cross-sectional study reported that the risk of elevated hs-CRP in overweight and obese groups is 1.2 and 1.7 times greater than in the normal weight group, respectively [75].
Obesity induces adipocyte dysfunction, with adipokine secretion and macrophage activation leading to pro-inflammatory cytokines such as TNF-α and IL-6, which are associated with elevated circulating hs-CRP levels [73]. These changes in the release of adipocytokines induce a state of systemic IR and low-grade inflammation. Similarly, Makki et al. demonstrated that elevated hs-CRP levels were related to increased abdominal fat [76]. Additionally, previous research has shown that diet-induced weight reduction is associated with reduced blood levels of IL-6, TNF-α, and hs-CRP [77]. Our findings support the view that obesity is responsible for a low degree of systemic inflammation. Therefore, controlling body weight is important to reduce the risk of hs-CRP-related diseases in the future.
Regarding IL-6 levels, the current study found a significant increase in IL-6 levels in all patient groups compared to the control group. However, there was no significant difference in IL-6 levels between the obese diabetes group and the obese hypertensive group when compared with the obese group. Obesity is a significant characteristic of metabolic syndrome, and the association between the two has been attributed to a chronic inflammatory process [78]. IL-6 is an important mediator of acute-phase reactions, and its levels are correlated with CRP levels [79]. As a result, both IL-6 and CRP are used clinically as biomarkers of inflammation. The present results are consistent with a study by Ismail et al. [80], noting statistically significantly higher IL-6 levels in the obese groups compared to the normal group. There was a statistically significant positive correlation between serum IL-6 and BMI. This finding is also consistent with El-Mikkawy et al.'s study, discovering that very significantly elevated circulating concentrations of IL-6 are observed in patients who were overweight or obese, regardless of whether they had chronic diseases [81]. Baikpour et al. found that IR is correlated with plasma levels of IL-6 in individuals with abdominal obesity; a strong positive correlation is also observed between serum IL-6 levels and BMI in healthy participants with obesity. According to Baikpour et al., IL-6 expression is greater in the adipose tissue of obese individuals than in that of non-obese individuals [82]. Hypothalamic upregulation of IL-6 receptor expression suggests that IL-6 may play a role in regulating energy intake and appetite [83].
Macrophages are the predominant immune cell population in human adipose tissue, constituting approximately 10% of the cellular composition of AT. The development of obesity is intricately linked with adipocyte hypertrophy, which triggers an inflammatory cascade that increases the number of adipose tissue macrophages (ATMs) [84] and alters their inflammatory profile. Obesity induces a shift in the distribution of T-cell subtypes, characterized by a decrease in anti-inflammatory regulatory T cells (Tregs) and T-helper (Th2) cells, alongside an increase in pro-inflammatory Th1 and Th17 cells. Consequently, an abundance of these pro-inflammatory T-cell subtypes is associated with elevated expression of IL-6 [85]. Finally, obesity and non-cardiovascular inflammatory diseases significantly influence serum IL-6 levels. The authors do not reach a consensus regarding IL-6’s potential as a biomarker for the onset of HTN and DM in healthy individuals.
Unexpectedly, we did not observe any differences in HIF-1α levels in obese patients, possibly due to population characteristics, such as age and sex. It may also be because physiological conditions are insufficient to stimulate HIF-1α, especially in chronic, subacute cases, as there may not be enough oxygen to clearly stimulate HIF-1α gene expression. Additionally, the effect of drug therapy may play a role; drugs used to treat diabetes and high blood pressure may affect the expression of HIF-1α. For example, several studies have shown that metformin (a common diabetes drug) can modify the response of HIF-1α in endothelial cells, thereby increasing its expression by reprogramming oxygen consumption in mitochondria, which leads to increased intracellular oxygen availability and enhances the degradation of HIF-1α [86, 87]. Several studies have also indicated that antihypertensive drugs (especially angiotensin antagonists, like ACE inhibitors and ARBs) can affect the gene expression of HIF-1α [88, 89]. The stage of the disease may also influence HIF-1α levels. In the early stages of chronic diseases, such as diabetes and HTN, HIF-1α may not be evident. A study showed that HIF-1α expression may be lower in disease states, especially in the early stages [90]. Ultimately, this result may be attributed to individual differences and biological variation. There may be individual variation among study participants in terms of genetics, lifestyle, or disease severity, which accounts for the differences between groups [91].
The main limitation of this study is the small sample size of the obese, hypertensive, type 2 diabetes, and control groups. Furthermore, this study was restricted to only one province. As a next step, we plan to expand the sample size and conduct research in multiple provinces. Additionally, future well-designed, gender-specific studies are needed to evaluate the role of hormones and inflammatory factors in the development of obesity-related complications.
Conclusion
Obese patients with type 2 diabetes and hypertension exhibit significantly higher levels of LEP and inflammatory factors and significantly lower levels of ADP compared to the control group.
Acknowledgments: The authors sincerely thank my family for their endless support and encouragement.
Ethical Permissions: Approvals from the scientific committee in the Chemistry Department, College of Sciences, University of Thi-Qar, as well as from the Thi-Qar Health Department, Training and Human Development Center, and Research Committee of the current study, were obtained. Oral consent for the study procedure was received from all participants enrolled in the study.
Conflicts of Interests: The authors declared no conflicts of interests.
Authors' Contribution: Abbas RK (First Author), Introduction Writer/Methodologist/Main Researcher/Discussion Writer/Statistical Analyst (50%); Alsaadi JHH (Second Author), Introduction Writer/Methodologist/Assistant Researcher/Discussion Writer/Statistical Analyst (50%)
Funding/Support: This research was self-funded.
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