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 Table of Contents  
Year : 2017  |  Volume : 7  |  Issue : 3  |  Page : 124-129

A demographic study on relation between uric acid and diabetes parameters in the Chhattisgarh State of India

1 Department of Biotechnology, National Institute of Technology, Raipur, Chhattisgarh, India
2 Department of Biochemistry, Pt. Jawahar Lal Nehru Memorial Medical College, Raipur, Chhattisgarh, India

Date of Web Publication15-Sep-2017

Correspondence Address:
Awanish Kumar
Department of Biotechnology, National Institute of Technology, Raipur - 492 010, Chhattisgarh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/AIHB.AIHB_34_17

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Objective: Epidemiological evidence suggest that conflicting data exist for the relation between serum uric acid (SUA) and various diabetes-associated parameters. Therefore, measurement of SUA levels could play a valuable role as predictor marker in early type 2 diabetics as well as a potent antioxidant therapeutic. This work is a small demographic study in the patients of Chhattisgarh to find a relation between the SUA level and diabetes parameters in diabetics and controls. Materials and Methods: This was a small sample set case–control study. Patients were divided into two groups, namely, control (n = 25) and type 2 diabetics (n = 30). Biochemical estimation of parameters was performed using commercially available enzymatic kits. Results: Plasma glucose, serum triglyceride, glycated haemoglobin and creatinine were higher in diabetic patients than in controls. SUA showed a significant lower level in test patients (2.97 ± 0.22) as compared to control (4.35 ± 0.64). A negative correlation of r = −0.8159 was obtained between SUA and plasma glucose levels. Conclusions: Results suggest that variation in uric acid (UA) levels from normal to pre-diabetes and diabetes condition could be an important biomarker. Further validations may pave the way for UA measurement as a diagnostic and prognostic marker in type 2 diabetes mellitus.

Keywords: Biomarker, serum, type 2 diabetes mellitus, uric acid

How to cite this article:
Thakur P, Kumar A, Patra PK, Kumar A. A demographic study on relation between uric acid and diabetes parameters in the Chhattisgarh State of India. Adv Hum Biol 2017;7:124-9

How to cite this URL:
Thakur P, Kumar A, Patra PK, Kumar A. A demographic study on relation between uric acid and diabetes parameters in the Chhattisgarh State of India. Adv Hum Biol [serial online] 2017 [cited 2022 Aug 15];7:124-9. Available from: https://www.aihbonline.com/text.asp?2017/7/3/124/214892

  Introduction Top

Globally, type 2 diabetes mellitus (T2DM) has become one of the most prevalent metabolic diseases among all races and ethnicities. It is one of the fastest expanding non-communicable diseases. There remains no place untouched by its premature morbidity and mortality as it is intricately at the crossroads of globalisation. The WHO reported it further that approximately 422 million people had diabetes in 2014 and caused 1.5 million deaths in 2012.[1] This affliction in such an alarming rate brings up an immediate need for research and insight to this chronic disease of global health concern.

Diabetes mellitus (DM) is basically a group of metabolic disorder encompassing derangement of carbohydrate, protein, lipid and various other metabolic pathways. On the one hand, type 1 DM (T1DM) is characterised by autoimmune cell mediated destruction of pancreatic β-cells leading to absolute insulin deficiency, thus, requiring exogenous insulin. T2DM is a prototypic polygenic combination of metabolic disorders resulting in defects in insulin secretion or insulin action or both; ultimately making cells insulin resistant. With the obese condition, there prevails wide range of intercalating genetic, environmental and recently found epigenetic factors contributing to T2DM aetiology.[2],[3] Although the hallmark feature is hyperglycaemia, the aberrancies are not limited to glucose and involve most processes of the intermediary metabolism. Thus, it is a multi-factorial and multi-consequential metabolic disorder.

Increasing evidence in both experimental and clinical studies has suggested that oxidative stress plays a major role in the pathogenesis of both types of DM. It is found that free radicals, which are highly reactive in nature, are formed disproportionately in diabetes by glucose oxidation, non-enzymatic glycation of proteins and the subsequent oxidative degradation of glycated proteins. This abnormally high levels of free radicals and the simultaneous decline of antioxidant defense mechanisms lead to damage of cellular organelles and enzymes, increased lipid peroxidation and development of insulin resistance.[4] These consequences of oxidative stress can promote the development of complications of DM. Thus, identifying the risk factors for developing T2DM is a key for its screening and prevention. Furthermore, monitoring the antioxidant shuttle in diabetes patients may help in augmented therapeutics of existing drugs.[4]

In this regard, uric acid (UA) and its urate shuttle is a potential area of the study. Studies have been carried out to find an association between serum uric acid (SUA) and glucose levels in diabetic patients. SUA is the metabolic end product of purine metabolism in humans. It is degraded by urate oxidase to allantoin that is freely eliminated in urine. UA has been reported as the most abundant aqueous antioxidant in humans and contributes as much as two-thirds of all free radical scavenging capacity in plasma. It is particularly effective in quenching hydroxyl, superoxide and peroxynitrite radicals, and may serve a protective physiological role by preventing lipid peroxidation.[5] It has long been hypothesised that hyperuricaemia might be a risk factor for the development of type 2 diabetes, but the casual association between hyperuricaemia and type 2 diabetes suffers conundrum and even varies from place to place.[6] UA can act as a prooxidant and it may thus be a marker of oxidative stress, but it may also have a therapeutic role as an antioxidant.[7],[8] UA cannot simply be viewed as a secondary phenomenon. UA and its changes during follow-up were related to corresponding changes in fasting and post-load glucose and insulin levels. There is a looping role of SUA in diabetes and this work is an attempt to correlate its level with various diabetic parameters in the subjects of Chhattisgarh.

Chhattisgarh is a state in central India with its capital as Raipur. Although, the prevalence rate of diabetes in Chhattisgarh is lower than other states of the country, the rapid urbanisation and changing lifestyle indicate an exponential increase in this rate in the near future (www.chhattisgrahstat.com). Furthermore, health reports suggest that with the interplay of genetic factors and lifestyle habits, the trend of diabetes here is closely related to compromised antioxidant levels as marker. Taking in account all the reported data, the present small scale demographic study was designed to look for the dependence of SUA levels on various diabetes parameters, considering the relevant clinical, biochemical and the anthropometric data.

  Materials And Methods Top

Study population

This study was carried out after obtaining approval from the Ethical Committee of NIT Raipur, Chhattisgarh and Pt. Jawahar Lal Nehru Memorial Medical College, Raipur, Chhattisgarh (Approval No. NITRR/IEC/9/2015). Informed consents were obtained from all the patients who were included in the study. A cross-sectional study was conducted on patients with known T2DM and healthy controls in the age group of 30–70 years. All the subjects were divided into two groups; Group I (n = 25; 15 males and 10 females; controls) Group II (n = 30; 18 males and 12 females; T2DM patients). A detailed history was taken from each patient. Fasting blood samples were drawn, and they were investigated for SUA, triglycerides, cholesterol, blood sugar and creatinine. Glycated hemoglobin (HbA1C) data were obtained from the hospital.

Sample collection

Overnight fasting samples were collected at around 10 am in clot activated tubes. Gel and clot activator tube is coated with micronised silica particles which causes blood to clot rapidly and the barrier gel effectively separate serum from fibrin and cells while preventing substance exchange between blood cell and serum. Samples may also be collected in tubes with anticoagulants such as ethylenediaminetetraacetic acid.

Serum isolation

The separating gel in the collection tube had intermediate density gradient between blood cells and blood plasma. Thus, on centrifuging the tube for 5–7 min at 5000 rpm, serum was separated as upper layer. It was carefully transferred to new vials. Storage conditions for sample were: 4°C (4–5 days) or −20°C (for 1–2 months).

Biochemical analysis

RMS Biochemistry Analyser was used for biochemical analysis of parameters. It is based on the measurement of a coloured compound formed in the test solution. It is a semi-automated analyser, i.e., initial part of the procedure pipetting of reagent and specimen, mixing and incubation is carried out externally and then photometric analysis was done by the analyser. Each sample was estimated for five parameters, namely, glucose, UA, triglyceride, creatinine and cholesterol using enzymatic kits from coral clinical systems. Except for creatinine, all other kits form red coloured quinoneimine dye on the action of peroxidase enzyme on H2O2. The intensity of colour formed was directly proportional to the amount of that component present in the sample.

Glucose estimation used glucose oxidase-peroxidase method, UA by Uricase/PAP (PAP = p-aminophenazone) method, cholesterol by CHOD/PAP (Cholestrol oxidase/p-aminophenazone) method, serum triglyceride by GPO/PAP (Glycerol-3-phosphate oxidase/p-aminophenazone) method. Creatinine kit used the modified Jaffe's method to determine creatinine in serum and urine.

Statistical analysis

Values were expressed as a mean ± standard error of the mean. All analysis was done using Windows Microsoft Excel and SPSS (Armonk, New York, U.S.). Student's t-test was used to compare the results of various parameters among the studied groups. P < 0.05 was considered as criterion for significance. Pearson's correlation analysis was performed for determining the degree of association between different parameters. A logistic regression analysis was also performed on the variables of each parameter.

  Results And Discussion Top

[Table 1] shows the summarised clinical and biochemical characteristics data. There was not a significant difference in the mean ages (in years) of sample sets of control and diabetics. Further, [Table 2] shows the dietary history of diabetic subjects. A significant difference (P < 0.05) can be observed in plasma glucose levels, UA levels, triglyceride levels and HbA1c of the controls and patients. [Figure 1],[Figure 2],[Figure 3],[Figure 4],[Figure 5] show graphical comparison of various parameters between control and T2DM patients. Since it is a demographic study, the variations also depend on the lifestyle, eating habits, environment of the geographic area. Accordingly, we observed in our results between control and T2DM subjects that a significant higher fasting plasma glucose levels can be seen in patients with type 2 diabetes (195.49 ± 19.32) than in controls (114.67 ± 4.22). Similarly, HbA1c (7.11 ± 0.24) and Triglyceride (421.21 ± 67.98) levels are also significantly higher in patients than in controls. Although cholesterol and creatinine levels were higher in diabetic samples than controls, the difference is not under significance criterion of P < 0.05.
Table 1: Clinical and biochemical characteristics of the study subjects

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Table 2: Dietary history of the diabetic subjects

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A significant lower level of UA in diabetic patients (2.97 ± 0.22) as compared to control group (4.35 ± 0.64) was observed [Figure 6]. A negative correlation was obtained between the fasting plasma glucose and the SUA levels (r = −0.8159) [Figure 7]. Finally, [Table 3] shows the Pearson's correlation matrix of all parameters and their interdependence on each other. It was also observed that there was a more negative correlation between plasma glucose and SUA in male subjects (r = −0.68) than in female subjects (r = −0.36).
Figure 1: Mean (± standard error of the mean), plasma glucose levels in control and type 2 diabetes mellitus subjects

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Figure 2: Mean (± standard error of the mean), glycated haemoglobin in control (normal glucose tolerance) and type 2 diabetes mellitus patients

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Figure 3: Mean (± standard error of the mean), serum triglyceride in control (normal glucose tolerance) and type 2 diabetes mellitus patients

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Figure 4: Mean (± standard error of the mean), total cholesterol in control (normal glucose tolerance) and type 2 diabetes mellitus patients

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Figure 5: Mean (± standard error of the mean), serum creatinine in control (normal glucose tolerance) and type 2 diabetes mellitus patients

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Figure 6: Mean (± standard error of the mean), serum uric acid in control (normal glucose tolerance) and type 2 diabetes mellitus patients

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Figure 7: Correlation (r = −0.8159) graph between plasma glucose and serum uric acid in diabetic patients

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Table 3: Pearson's correlation matrix of related parameters

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Chhattisgarh was established as a separate province in India on November 1, 2000. Since then, it has witnessed many transitions in lifestyle and eating habits of its population. Due to continuous development and urbanisation, there has been an increase in chronic metabolic diseases such as hypertension and diabetes. Thus, though there have been many reporting on the association of plasma glucose level and SUA, the results are expected to show some variations in different population sets due to numerous previously mentioned factors. Some studies have reported a positive association between high SUA levels and diabetes,[9],[10],[11],[12],[13] whereas some reported no association,[14] or an inverse relationship.[15],[16] In this, though a small sample size study was done, a negative correlation has been obtained. The general accepted range for SUA is 3.6-8.4 mg/dl for males and 2.9-7.5 mg/dl for females.[17]

Different theories may be used to reason this reduction of UA level in diabetic subjects as compared to controls. Lytvyn et al.[18] have reported that glycosuria, and not hyperglycaemia, was responsible for increased UA excretion in patients with T1DM due to activation of glucose-mediated GLUT9 isoform 2 in proximal tubules while González-Sicilia et al.[19] also reported that T1DM patients with poorly controlled glycaemia show hyperuricosuria and hypouricaemia. They found an inverse relation between glycaemia and SUA level. Hayden et al.[20] reviewed the antioxidant-prooxidant shuttle of UA and reported that elevated SUA attributed to endothelial dysfunction and elevated oxidative stress in the glomerulus and fibrotic remodelling of kidney and glomerulus.

Talking about the negative correlation of plasma glucose level and SUA concentration, there comes a complex interplay of factors. The looping dual role of UA can be reasoned by understanding its pro-oxidant-anti-oxidant shuttle. UA, in the normal physiological microenvironment, functions as an antioxidant by modifying the activity of the enzyme xanthine oxidase, which in stress can become a dangerous source of free radicals. It is reported to exist in two interconvertible forms, xanthine dehydrogenase and xanthine oxidase. The latter uses molecular oxygen as an electron acceptor, and it generates a superoxide anion with other reactive oxygen species, thus favoring an antioxidant – prooxidant urate redox shuttle.[20],[21] Furthermore, UA can prevent peroxynitrite-induced protein nitrosation, lipid and protein peroxidation, and inactivation of tetrahydrobiopterin, a cofactor necessary for nitric oxide synthase (NOS). UA also protects low-density lipoprotein from Cu2+-mediated oxidation. Together, these antioxidant actions underlie the protective effects of UA action.[21] As the risk for diabetes increases, UA level increase. This increased SUA acts as a biomarker for initial onset of diabetes and a first-line protective response against oxidative stress which is the primary manifestation of alterations in metabolic pathways caused by hyperglycaemia. Further, UA has been reported to induce diabetes-related changes due to change in vascular health and inflammation, activation of rennin-angiotensin system and associated endothelial dysfunction. Increased SUA is also said to induce mitochondrial oxidative stress in pancreatic β-cell.[22]

Furthermore, UA has been reported to worsen the insulin resistance in animal models by inhibiting nitric oxide (NO) which is essential for glucose-mediated insulin release, and insulin-mediated glucose uptake. It has been reported that diabetic patients with hyperlipidaemia and hyperuricaemia show low levels of serum NO. This decrease in bioavailability of NO may be due to inactivation of NO by an irreversible reaction resulting in the formation of 6-aminouracil or due to uncoupling of NOS complex.[23] High fructose intake has been shown to increase the level of UA by its direct metabolism and nucleotide turnover. UA has, in turn, been shown to inhibit AMP-dependent kinase and stimulate hepatic lipogenesis. The mechanism behind this has been reported to be an intracellular oxidative burst-mediated by UA. UA has been reported to induce an oxidative burst in various cells such as endothelial cells, adipocytes, vascular smooth muscle cells, hepatocytes and a few more and results in their damage. UA also increases the expression of ketohexokinase in hepatocytes, which is the first enzyme in fructose metabolism, increasing further accumulation of triglyceride in hepatocytes.[24] The study results from this study were consistent with another large population study performed in US (race and ethnicity independent) by Bandaru and Shankar[25] where the researchers concluded that higher SUA was inversely associated with diabetes. A possible mechanism behind this inverse relation could be the inhibition of tubular reabsorption of UA during glycosuria.

Since hyperglycaemia manifests many other deteriorating conditions, other diabetes parameters such as HbA1c, serum triglycerides, creatinine, cholesterol directly or indirectly affect SUA level and antioxidant in a subject as a whole. This can also be inferred from the results of this study. Summing up, SUA forms a cause and effect circle in the form of pro-oxidant-antioxidant shuttle. It would not be an exaggeration to quote that measurement of SUA is a very important diagnostic and as well as prognostic aspect for diabetes management in a clinical standpoint. Further, in a population like Chhattisgarh which has just started its road towards development, preventive and curative measures involving antioxidant therapeutics might help in better diabetes treatment.

  Conclusion Top

The present patient-based study was conducted in a small population group in Chhattisgarh state of India. In the study, we observed that there is a negative correlation between the fasting plasma glucose and serum uric acid (SUA) level in diabetic patients. As discussed and supported with proper references cited in the article, there have been many previous studies that have supported such a negative correlation between SUA and fasting plasma glucose. As a contrast, there have been a few other studies that have also found a positive correlation. But as always is the case, finding a relation among biomarkers or factors with each other for a cause-result relationship is a long study. As discussed, since uric acid is considered as one of the most potent physiological antioxidant, its normal level is considered good for the human body. But it is also seen in various studies that high SUA can act as prooxidant too. Thus, finding a cause-result relationship between SUA and fasting plasma glucose can lead us to an important pathophysiological consideration. Our small-sized population based studies has provided another supportive lead to certain empirical studies that suggest a negative correlation between fasting glucose and serum uric acid level suggesting that less than normal uric acid may make the patient susceptible towards hyperglycemia that may lead to long term diabetes.

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Conflicts of interest

There are no conflicts of interest.

  References Top

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González-Sicilia L, García-Estañ J, Martínez-Blázquez A, Fernández-Pardo J, Quiles JL, Hernández J. Renal metabolism of uric acid in type I insulin-dependent diabetic patients: Relation to metabolic compensation. Horm Metab Res 1997;29:520-3.  Back to cited text no. 19
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Shani M, Vinker S, Dinour D, Leiba M, Twig G, Holtzman EJ, et al. High normal uric acid levels are associated with an increased risk of diabetes in lean, normoglycemic healthy women. J Clin Endocrinol Metab 2016;101:3772-8.  Back to cited text no. 22
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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]

  [Table 1], [Table 2], [Table 3]


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