Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder characterized by persistent hyperglycemia due to insulin resistance and progressive β-cell dysfunction. It accounts for approximately 90–95% of all diabetes cases globally, posing a significant public health challenge. According to the International Diabetes Federation (IDF), the global prevalence of diabetes is projected to rise from 8.3% in 2011 to 9.9% by 2030, affecting over 438 million individuals. The burden is particularly high in low- and middle-income countries, with nearly 80% of diabetes cases reported in nations such as China and India. Despite its widespread prevalence, nearly 50% of individuals with diabetes remain undiagnosed, leading to late-stage complications, including cardiovascular disease, nephropathy, neuropathy, and retinopathy. Given the progressive nature of the disease, there is a critical need for early diagnostic markers that can aid in risk assessment, disease monitoring, and therapeutic interventions.[1-6] Adiponectin, an adipocyte-derived hormone, plays a crucial role in glucose homeostasis, lipid metabolism, and insulin sensitivity. It enhances insulin action by activating AMP-activated protein kinase (AMPK) and peroxisome proliferator-activated receptor-alpha (PPAR-α), thereby promoting glucose uptake, reducing hepatic gluconeogenesis, and facilitating fatty acid oxidation. Notably, plasma adiponectin levels are inversely correlated with obesity, insulin resistance, and T2DM, making it a potential biomarker for metabolic disorders. Hypoadiponectinemia has been implicated in metabolic syndrome, dyslipidemia, and cardiovascular disease, suggesting that alterations in serum adiponectin levels may reflect disease severity and progression in T2DM. Despite its promising role, the clinical utility of adiponectin as a predictive biomarker for T2DM remains underexplored, necessitating further research to establish its diagnostic and prognostic value.[7-18]

This study aims to quantitatively estimate serum adiponectin levels in individuals with T2DM and evaluate its association with key metabolic parameters, including fasting blood glucose (FBS), glycated hemoglobin (HbA1c), lipid profile, and age. By investigating the relationship between adiponectin and metabolic dysfunction, this research seeks to elucidate its potential role in early diabetes detection, risk stratification, and disease monitoring. Understanding these associations could provide valuable insights into the pathophysiology of T2DM and aid in the development of targeted therapeutic strategies.

Study Design and Setting

This observational case-control study was conducted in the Department of Biochemistry, Dr. Rajendra Prasad Government Medical College and Hospital, Tanda, Kangra, Himachal Pradesh, India, after obtaining ethical clearance from the Institutional Ethics Committee (Approval No.: HFW-H DRPGMC/Ethics/2023/122, dated 13-10-2023). The study aimed to quantitatively estimate serum adiponectin levels in individuals with Type 2 Diabetes Mellitus (T2DM) and evaluate its association with key metabolic parameters.

Study Population and Recruitment

A total of 100 participants (50 T2DM cases and 50 healthy controls) were recruited from the centralized collection center and outpatient clinic of the hospital. All participants provided written informed consent before enrollment. Inclusion criteria encompassed individuals aged 18–60 years diagnosed with T2DM (cases) or without any metabolic disorder (controls). Exclusion criteria included pregnant or lactating women, individuals with chronic illnesses (e.g., tuberculosis, cancer, HIV/AIDS), and those on medications affecting glucose metabolism or adiponectin levels.

Sample Collection and Processing

A 5 mL venous blood sample was collected aseptically from the median cubital vein using a disposable syringe. Of this, 2 mL was transferred to an EDTA tube for HbA1c estimation, while 3 mL was collected in a serum separator tube (SST) for fasting blood glucose (FBS), lipid profile, and adiponectin estimation. Blood in SST tubes was allowed to clot at room temperature for 15–20 minutes before being centrifuged at 2000 rpm for 10 minutes. The clear supernatant serum was stored at −20°C until further analysis.

Biochemical Analysis

Serum adiponectin levels were measured using an Enzyme-Linked Immunosorbent Assay (ELISA) based on a sandwich immunoassay principle. The assay involved binding monoclonal anti-adiponectin antibodies to microplate wells, followed by detection with a biotin-labeled secondary antibody and streptavidin-HRP. The colorimetric reaction was quantified at 450 nm, and internal quality controls ensured assay reliability. Fasting blood glucose (FBS) was estimated using the glucose oxidase-peroxidase (GOD-POD) method on a fully automated XL-640 chemistry analyzer (Transasia). HbA1c levels were determined using NycoCard Reader (Alere Technologies), a boronate affinity chromatography-based method, which selectively binds glycated hemoglobin.

A comprehensive metabolic panel was performed, including lipid profile and renal and liver function tests. Total cholesterol was measured using the cholesterol oxidase-peroxidase method, triglycerides by the glycerol phosphate oxidase method, and HDL cholesterol using immunoinhibition. LDL and VLDL levels were calculated using the Friedewald equation. Renal function was assessed via serum urea (Urease-GLDH method), creatinine (Modified Jaffe’s method), and uric acid (Uricase-peroxidase method). Liver function was evaluated by measuring SGOT (AST) and SGPT (ALT) using IFCC methods, and alkaline phosphatase (ALP) using the AMP method. All biochemical parameters were analyzed on the XL-640 (Erba, Mannheim, Germany) autoanalyzer using standardized reagents and daily calibration protocols.

Statistical Analysis

Data were entered into Microsoft Excel and analyzed using SPSS version 25.0. Continuous variables were expressed as mean ± standard deviation (SD), while categorical variables were presented as frequency and percentages. An independent t-test was performed to compare serum adiponectin levels between T2DM cases and controls. Pearson correlation analysis was conducted to assess the relationship between serum adiponectin and metabolic parameters (HbA1c, lipid profile, fasting glucose, and renal function markers). A p-value < 0.05 was considered statistically significant.

Ethical Considerations

The study was conducted in adherence to the Declaration of Helsinki ethical guidelines. Written informed consent was obtained from all participants, ensuring confidentiality and voluntary participation. Samples were used exclusively for research purposes, and all collected data were anonymized to maintain participant privacy.

The present study was conducted at the Department of Biochemistry, Dr. Rajendra Prasad Government Medical College, Kangra at Tanda, to evaluate the serum levels of adiponectin, an adipose-specific protein, in individuals with Type 2 Diabetes Mellitus (T2DM) and compare them with healthy non-diabetic controls. A total of 100 participants were enrolled, comprising 50 T2DM patients and 50 age- and sex-matched controls. The case group consisted of 21 males and 29 females (M:F = 0.7:1), while the control group included 20 males and 30 females (M:F = 0.6:1). The study aimed to investigate the association between serum adiponectin levels, glycemic control, and metabolic parameters in diabetic and non-diabetic individuals.

This table-1 presents the demographic distribution and lifestyle factors among the case (T2DM patients) and control (healthy individuals) groups. The sex distribution shows a slightly higher prevalence of diabetes in females, but the difference is not statistically significant (p = 0.839). The occupation distribution indicates that a higher proportion of housewives were diabetic, but this association is also non-significant (p = 0.155). Similarly, dietary habits were comparable between groups, with vegetarians being more prevalent in the diabetic group, though the difference is not significant (p = 0.137). However, a statistically significant difference was observed in smoking behavior (p = 0.022), where occasional smoking was reported only in diabetic individuals. Moreover, alcohol consumption showed a significant difference (p = 0.001), with a higher prevalence of occasional drinkers among diabetics, potentially indicating lifestyle-related risk factors for T2DM.

Table 1: Demographic and Lifestyle Characteristics of Case and Control Groups

This table-2 highlights the key biochemical differences between the case and control groups. The mean age of the T2DM group (50.7 years) was significantly higher than that of the control group (45.6 years) (p = 0.017), indicating that older individuals are more prone to developing diabetes. Serum adiponectin levels were significantly lower in the diabetic group (p < 0.0001), confirming its role in insulin sensitivity and metabolic regulation. Fasting blood sugar (FBS) and HbA1c were markedly elevated in diabetic patients (p < 0.0001), reflecting impaired glucose control and disease progression. Additionally, serum urea and uric acid levels were significantly higher in the diabetic group, suggesting early renal involvement (p = 0.003 and 0.013, respectively), while creatinine levels showed no significant difference (p = 0.899), indicating preserved kidney function in most patients.

Table 2: Mean and Standard Deviation Values of Key Biochemical Parameters

This table-3 compares the lipid and liver function parameters between the case and control groups. Total cholesterol levels were significantly higher in the diabetic group (p = 0.028), reinforcing the link between T2DM and dyslipidemia. However, triglycerides and HDL levels did not show significant differences, suggesting that lipid abnormalities in T2DM patients may vary based on individual metabolic factors. Liver enzyme markers SGOT and SGPT were elevated in diabetics but did not reach statistical significance (p = 0.210 and 0.076, respectively), whereas alkaline phosphatase (ALP) was significantly higher (p < 0.0001), indicating possible hepatic stress or metabolic changes associated with T2DM. Total and direct bilirubin levels were similar between both groups (p = 0.723 and 0.321, respectively), suggesting that liver dysfunction is not a predominant feature in this diabetic cohort.

Table 3: Lipid Profile, Liver Function, and Bilirubin Parameters

This table-4 explores the relationship between serum adiponectin levels and key metabolic indicators. In diabetics, adiponectin showed a weak negative correlation with age (-0.139, p = 0.335), which was not significant, suggesting that age alone may not be a primary determinant of adiponectin levels. However, a significant negative correlation was found between adiponectin and HbA1c (-0.381, p = 0.006), reinforcing the role of adiponectin in glycemic control. Interestingly, adiponectin did not show a strong correlation with FBS in either group (p = 0.069 in diabetics and p = 0.57 in controls), indicating that its impact on glucose metabolism may be more evident in long-term markers like HbA1c rather than fasting glucose levels.

Table 4: Correlation of Adiponectin with Age, FBS, and HbA1c

This table-5 evaluates the relationship between adiponectin levels and lipid parameters in diabetic and control groups. Adiponectin showed a negative correlation with total cholesterol and triglycerides in diabetics (-0.167 and -0.083, respectively), but these associations were not statistically significant (p = 0.246 and 0.568). Similarly, in controls, a weak positive correlation was observed between adiponectin and cholesterol (0.237, p = 0.097), though it did not reach significance. HDL showed a mild negative correlation with adiponectin in diabetics (-0.053, p = 0.715) and controls (-0.238, p = 0.096), suggesting that adiponectin’s beneficial effects on lipid metabolism may be influenced by additional metabolic factors. These findings align with previous studies indicating that while adiponectin plays a role in lipid homeostasis, its impact is not always consistent across different populations.

Table 5: Correlation of Adiponectin with Lipid Profile

Type 2 Diabetes Mellitus (T2DM) is a complex and chronic metabolic disorder marked by persistent hyperglycemia, insulin resistance, and progressive pancreatic β-cell dysfunction. It remains a major global health concern, with an increasing prevalence driven by factors such as genetic predisposition, obesity, sedentary lifestyles, and dietary habits. The interplay of insulin resistance, chronic inflammation, and oxidative stress plays a crucial role in the pathogenesis of T2DM, further exacerbating metabolic dysregulation and increasing the risk of long-term complications.[1-6]

Our study, conducted at the Department of Biochemistry, Dr. Rajendra Prasad Government Medical College, examined 50 T2DM patients and 50 healthy controls. The findings revealed that T2DM was more prevalent in individuals above 50 years of age, with most diagnoses occurring between 45 and 50 years. Males were found to be more frequently affected, which aligns with the observations of [19,20], who reported a higher incidence in males and earlier disease onset. Notably, microvascular complications were prevalent in individuals with diabetes duration exceeding 10 years, reinforcing the well-documented progressive nature of T2DM and its complications.

A key focus of this study was the quantitative estimation of serum adiponectin levels alongside routine biochemical parameters. The Body Mass Index (BMI) of the individuals in my case study was less than 25 which is considered within the normal range. Accordingly, Adiponectin values ranged from 5 to 37 µg/mL, with approximately 50% of the individuals showing a decrease in adiponectin levels, suggesting a strong link between hypoadiponectinemia and insulin resistance, a hallmark of T2DM. These findings align with previous research [11,21], which established an inverse relationship between adiponectin and insulin resistance, inflammation, and cardiovascular risk. Additionally, adiponectin levels were negatively correlated with fasting blood glucose (FBS) and HbA1c, reinforcing its role as a potential biomarker for early diabetes detection and disease severity assessment.

Significant elevations in fasting blood sugar (FBS) and glycated hemoglobin (HbA1c) levels were observed in diabetic patients compared to controls, consistent with findings by previous studies.[22] Elevated FBS levels indicate impaired glucose regulation, highlighting the need for strict glycemic control to prevent diabetes-related complications. The progressive increase in HbA1c levels, correlating with disease duration, underscores the importance of early lifestyle modifications and pharmacological interventions to slow disease progression.

Adiponectin, an adipocyte-derived hormone, plays a pivotal role in glucose and lipid metabolism, primarily by enhancing insulin sensitivity and exerting anti-inflammatory effects. Our study demonstrated that lower adiponectin levels were significantly associated with higher cholesterol and triglyceride levels in T2DM patients. These results are supported [22], who reported that adiponectin positively influences HDL cholesterol levels, independent of BMI and insulin resistance. However, some studies, including [23], have shown stronger correlations between adiponectin and lipid parameters, suggesting that a more detailed stratification based on obesity and metabolic syndrome status could further clarify this relationship.

An interesting observation in our study was the negative correlation between adiponectin levels and age in the diabetic group, suggesting that aging may contribute to declining adiponectin levels. This finding is in agreement with [20], who reported an age-related decrease in adiponectin levels, potentially explaining the increased risk of metabolic disorders, including T2DM and cardiovascular diseases, in older populations. However, in contrast to certain studies such as [24], which reported a strong correlation between adiponectin levels and total body fat, our study found that decreased adiponectin levels in T2DM were independent of BMI. This discrepancy may stem from differences in study populations, body composition assessments, and ethnic variations.

Moreover, while our study noted a higher prevalence of T2DM in males, the literature presents varying trends regarding gender susceptibility. Some studies, including [20], suggest a greater association between adiponectin and diabetes risk in females under specific conditions, potentially influenced by hormonal variations and lifestyle differences. Further research is needed to clarify these gender-specific associations and their implications for diabetes risk assessment.

Although our study identified correlations between adiponectin and lipid levels, the strength of these associations was moderate. Studies like [23] reported that low adiponectin levels were strongly linked to severe insulin resistance, particularly in obese individuals. These differences emphasize the need for larger cohort studies incorporating obesity and metabolic syndrome stratifications to better understand adiponectin's role in metabolic regulation.

Our study highlights the strong association between lower adiponectin levels and T2DM, emphasizing its potential as an early diagnostic and prognostic biomarker. The observed correlations between adiponectin, glycemic markers (FBS, HbA1c), and lipid profiles suggest that adiponectin may serve as a valuable indicator of metabolic dysfunction in diabetes. Given its anti-inflammatory and insulin-sensitizing properties, adiponectin emerges as a promising target for therapeutic interventions aimed at improving insulin sensitivity and reducing cardiovascular risk.

Future research should explore the underlying mechanisms of adiponectin regulation, its interaction with metabolic pathways, and its potential therapeutic applications in diabetes management. By expanding our understanding of adiponectin’s role in metabolic health, we can develop more effective strategies for the prevention, early detection, and treatment of T2DM.

The authors declare that they have no conflict of interest

No funding sources

The study was approved by the Dr. Rajendra Prasad Government Medical College ,Tanda At Kangra, Himachal Pradesh.

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