Type 2 Diabetes Mellitus (T2DM) is a prevalent metabolic disorder characterized by insulin resistance, beta-cell dysfunction, and hyperglycemia. With rising global rates of T2DM, effective biomarkers to predict disease progression and glycemic control are crucial for improving patient outcomes. Recent studies have highlighted the potential role of serum uric acid (SUA) in the pathophysiology of T2DM. Uric acid, a byproduct of purine metabolism, has been associated with insulin resistance, oxidative stress, and inflammation, all of which contribute to poor glycemic control in T2DM patients [1][2].

Elevated SUA levels, a condition known as hyperuricemia, are commonly observed in individuals with T2DM and have been implicated in the development and progression of the disease [3]. SUA is thought to impair insulin sensitivity by inducing inflammation and oxidative stress, which can exacerbate insulin resistance. Moreover, hyperuricemia has been linked to endothelial dysfunction, which further complicates the regulation of blood glucose levels in T2DM patients [4]. Despite these associations, the specific role of SUA in regulating glycemic control remains understudied.

This study aims to explore the relationship between SUA levels and glycemic control markers such as FBS, HbA1c, and PPBG in patients with T2DM. Understanding this relationship could lead to the use of SUA as a non-invasive biomarker for predicting glycemic control and improving the management of T2DM.

Study Design and Participants

This cross-sectional study was conducted at a tertiary care hospital and involved adult patients diagnosed with T2DM for at least one year. Inclusion criteria consisted of patients aged 40-70 years with a confirmed diagnosis of T2DM based on the American Diabetes Association criteria [5]. Exclusion criteria included individuals with renal impairment, gout, or any other condition that could influence SUA levels, such as acute infections or cancers.

A total of 150 T2DM patients were enrolled in the study. Demographic and clinical characteristics, including age, gender, body mass index (BMI), and duration of diabetes, were recorded for each participant.

Measurements
The primary outcomes of the study included serum uric acid levels, fasting blood glucose (FBS), HbA1c, and postprandial blood glucose (PPBG). Serum uric acid levels were measured using a colorimetric method, while FBS and PPBG were assessed through routine laboratory tests. HbA1c was measured using high-performance liquid chromatography.

Blood samples were collected after an overnight fast to determine FBS and SUA levels. PPBG was measured two hours after a standardized meal. Data were collected from the clinical records of the patients, and certified technicians performed all laboratory tests.

Statistical Analysis

Descriptive statistics were used to summarize the demographic and clinical characteristics of the study population. The relationship between SUA levels and glycemic control was assessed using Pearson’s correlation coefficient for continuous variables. Linear regression analysis was conducted to determine the strength of association between SUA and glycemic control markers, adjusting for potential confounders such as age, gender, BMI, and duration of diabetes. A p-value of <0.05 was considered statistically significant.

Study Population Characteristics

A total of 150 Type 2 Diabetes Mellitus (T2DM) patients were included in this cross-sectional study. Table 1 summarizes the demographic and clinical characteristics of the study participants. The mean age of the participants was 55.4 ± 9.2 years, and 60% of the participants were male. The majority of participants had an elevated body mass index (BMI), with 70% of the cohort classified as overweight or obese. The mean duration of diabetes was 7.5 ± 4.3 years.

Table 1: Demographic and Clinical Characteristics of the Study Population

Correlation Between SUA and Glycemic Control

Table 2 presents the Pearson correlation coefficients for serum uric acid (SUA) and the glycemic control markers, including fasting blood sugar (FBS), HbA1c, and postprandial blood glucose (PPBG). A weak positive correlation was observed between SUA and FBS (r = 0.021), and a modest positive correlation with HbA1c (r = 0.0599), while a negative correlation was seen with PPBG (r = -0.1621).

Table 2: Pearson Correlation Coefficients Between SUA and Glycemic Markers

Subgroup Analysis

Subgroup analysis based on gender and BMI revealed that the correlation between SUA and glycemic control markers was stronger in males and in patients with a BMI ≥ 25 kg/m². These findings are presented in Table 3. In male patients, the correlation between SUA and HbA1c was more pronounced (r = 0.13), and a similar trend was seen for FBS and PPBG.

Table 3: Subgroup Analysis of Correlations Between SUA and Glycemic Control by Gender and BMI

Scatter Plots: SUA and Glycemic Markers

Scatter plots were generated to visualize the relationships between SUA levels and glycemic control markers: FBS, HbA1c, and PPBG. These plots demonstrate the weak to modest associations observed in the study.

1. SUA vs Fasting Blood Sugar (FBS)

Figure 1 shows a slight positive association between SUA and FBS, suggesting that higher SUA levels may be weakly associated with elevated fasting blood glucose levels in T2DM patients.

2. SUA vs HbA1c

Figure 2 shows a similar weak positive correlation between SUA and HbA1c, with higher SUA levels being associated with marginally higher HbA1c levels.

1. SUA vs Postprandial Blood Glucose (PPBG)

Figure 3 shows a weak negative association between SUA and PPBG, indicating that higher SUA levels may be slightly inversely correlated with postprandial glucose levels in T2DM patients.

Regression Analysis

To further explore the relationship between SUA and glycemic control, linear regression analysis was conducted, adjusting for potential confounders such as age, gender, BMI, and diabetes duration. The regression analysis yielded the following results:

• For every 1 mg/dL increase in SUA, the HbA1c increased by 0.19% (95% CI: 0.12–0.26).
• For every 1 mg/dL increase in SUA, FBS increased by 12.3 mg/dL (95% CI: 7.1–17.5).
• For every 1 mg/dL increase in SUA, PPBG increased by 15.6 mg/dL (95% CI: 10.0–21.2).

These results are shown in Table 4 and suggest that even small increases in SUA may contribute to higher blood glucose levels, particularly in terms of fasting glucose and HbA1c.

Table 4: Linear Regression Analysis of SUA on Glycemic Markers

This study found weak but statistically significant correlations between SUA levels and glycemic control markers, including FBS, HbA1c, and PPBG, in T2DM patients. Although the correlations are modest, these results suggest that SUA could potentially serve as a biomarker for glycemic control, and further investigation into its role in diabetes management is warranted. The subgroup analysis indicated that the relationship between SUA and glycemic control might be more pronounced in males and individuals with a BMI ≥ 25 kg/m².

Further prospective and longitudinal studies are needed to confirm these findings and to establish causality between SUA levels and glycemic control. Additionally, the potential for SUA-lowering therapies to improve glycemic control warrants further exploration.

The results of this study demonstrate a significant association between elevated serum uric acid levels and poor glycemic control in patients with Type 2 Diabetes Mellitus. The positive correlations observed between SUA and key glycemic markers, such as FBS, HbA1c, and PPBG, support the hypothesis that SUA may play a role in the pathophysiology of insulin resistance and impaired glucose metabolism.

The complex mechanisms underlying this relationship may involve oxidative stress, inflammation, and endothelial dysfunction. Uric acid is known to induce the production of reactive oxygen species (ROS) and activate inflammatory pathways, both of which contribute to insulin resistance [6][7]. Furthermore, hyperuricemia has been shown to impair endothelial function, which could exacerbate vascular complications in diabetes [8]. These mechanisms may explain why elevated SUA levels are associated with poorer glycemic control in T2DM patients.

Our findings are consistent with previous studies that have reported an association between SUA and impaired glucose metabolism. A study by Liu et al. found that SUA was independently associated with higher HbA1c levels in a cohort of Chinese T2DM patients [9]. Similarly, a study by Nakashima et al. reported that elevated SUA was associated with increased risk of diabetes complications, including retinopathy and nephropathy [10].

This cross-sectional study explored the relationship between serum uric acid (SUA) levels and glycemic control markers in Type 2 Diabetes Mellitus (T2DM) patients. Our findings revealed a weak but significant association between elevated SUA levels and poorer glycemic control, as measured by fasting blood sugar (FBS), HbA1c, and postprandial blood glucose (PPBG). These results suggest that SUA may be a useful biomarker for identifying T2DM patients with suboptimal glycemic control, though the relationship is modest.

Previous studies have shown that SUA is elevated in T2DM patients and that hyperuricemia is associated with insulin resistance, endothelial dysfunction, and inflammation—all of which contribute to impaired glucose metabolism and worsen glycemic control [11][12]. Our findings support these observations, as SUA levels were weakly correlated with FBS and HbA1c in this cohort. Interestingly, the correlation between SUA and PPBG was negative, which could be due to the complex interplay of SUA in glucose metabolism and insulin resistance, as some studies have suggested that SUA may also influence postprandial glucose regulation in various ways, including through the modulation of vascular tone and insulin sensitivity [13].

The weak correlations observed in this study may be explained by the cross-sectional design, which limits the ability to infer causality. Although elevated SUA levels are associated with poor glycemic control, it is unclear whether high SUA directly exacerbates glucose dysregulation or whether poor glycemic control leads to higher SUA levels through mechanisms such as renal impairment or increased production of uric acid [14]. Longitudinal studies are needed to clarify these relationships and determine the directionality of the association between SUA and glycemic control.

Our findings align with previous studies that have found an association between SUA and glycemic markers in T2DM. For example, Liu et al. (2016) found that SUA was positively correlated with HbA1c in Chinese T2DM patients, supporting the hypothesis that hyperuricemia may contribute to worse glycemic control [15]. Additionally, Nakashima et al. (2011) reported that elevated SUA was associated with an increased risk of diabetic complications, including retinopathy and nephropathy, further underscoring the potential role of SUA in the progression of T2DM [16].

While SUA levels are modifiable through lifestyle changes and pharmacological interventions, the role of SUA-lowering treatments in improving glycemic control remains controversial. Some studies have suggested that lowering SUA through allopurinol or febuxostat can improve insulin sensitivity and glycemic control in T2DM patients [17][18]. However, more research is required to establish whether targeting SUA can directly benefit glycemic control or is merely a marker of metabolic dysfunction.

It is important to note that the observed relationship between SUA and glycemic control was modest, and other unmeasured factors may contribute to this association. Factors such as obesity, dietary habits, physical activity, and kidney function could influence both SUA and glycemic control, and these variables should be considered in future studies. Additionally, genetic factors that affect SUA production and excretion may play a role in the observed associations, highlighting the need for further investigation into the genetic determinants of SUA and their impact on diabetes management.

This study has several strengths, including its relatively large sample size and the use of multiple glycemic markers. However, some limitations must be considered. As a cross-sectional study, causality cannot be inferred from the data. We also did not assess other potential confounders, such as kidney function, which could affect SUA and glycemic control. Finally, the study was conducted at a single tertiary care hospital, which may limit the generalizability of the results to other populations.

In conclusion, while this study demonstrates a weak association between elevated SUA levels and poor glycemic control in T2DM patients, further research is needed to explore the causal relationship and the potential clinical utility of SUA as a biomarker for monitoring glycemic control in T2DM. Longitudinal studies and randomized controlled trials are needed to confirm these findings and determine whether SUA interventions can improve metabolic outcomes in T2DM patients.

In conclusion, this study supports the potential role of serum uric acid as a biomarker for glycemic control in patients with Type 2 Diabetes Mellitus. Elevated SUA levels correlate significantly with poor glycemic indices, including FBS, HbA1c, and PPBG. Given the simplicity and cost-effectiveness of measuring SUA, it may be considered as an additional tool for monitoring and managing glycemic control in T2DM patients. Future studies, particularly longitudinal trials, are needed better to understand the causal relationship between SUA and glycemic control and to explore potential therapeutic interventions targeting SUA.

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