Association between tumour necrosis factor-{alpha} G-308A polymorphism and risk of nephropathy in obese Chinese type 2 diabetic patients

Ying Wang, Maggie C. Y. Ng, Wing-Yee So, Ronald Ma, Gary T. C. Ko, Peter C. Y. Tong and Juliana C. N. Chan

From the Division of Endocrinology, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR

Correspondence and offprint requests to: Dr Wing-Yee So, MBChB, MRCP, Department of Medicine & Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR. Email: wingyeeso{at}cuhk.edu.hk



   Abstract
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Background. The G-308A polymorphism in the promoter region of the tumor necrosis factor alpha (TNF-{alpha}) gene has been reported to be associated with insulin resistance and obesity, both of which may increase the risk of diabetic nephropathy. We hypothesized that this polymorphism might interact with obesity to affect development of diabetic nephropathy.

Methods. A consecutive cohort of 1281 Chinese type 2 diabetic patients was enrolled for analysis. Genotyping of TNF-{alpha} G-308A polymorphism was performed using a PCR-based RFLP method with NcoI digestion. The mean value of the albumin creatinine ratio (ACR) of a random spot urine sample and a timed urinary collection was used to determine albuminuric status. Diabetic nephropathy was defined as serum creatinine ≥150 µmol/L and/or mean ACR ≥25 mg/mmol. Obesity was defined as body mass index ≥25 kg/m2 using Asian criteria.

Results. The G-308A polymorphism was not associated with either obesity or nephropathy. Clinical characteristics were similar between GG and GA/AA genotype carriers. Amongst the obese patients, GG genotype carriers had a higher median (interquartile range) urinary ACR [3.16 (0.70, 59.10) vs 1.28 (0.48, 12.28) mg/mmol; p = 0.01] and albumin excretion rate [38.7 (12.1, 620.3) vs 21.4 (8.9, 224.0) µg/min, p = 0.03] than GA/AA carriers. On multiple logistic regression analysis, compared with non-obese GA/AA carriers, obese subjects with the GG genotype had a 2.5-fold increased risk (95% CI: 1.04–6.03; P = 0.04) of nephropathy after adjustment for confounding factors. Other independent factors for diabetic nephropathy included male sex, systolic blood pressure, triglycerides (logarithmically transformed value), and the presence of cardiovascular and microvascular complications.

Conclusion. Our findings suggest that the GG genotype of TNF-{alpha} G-308A polymorphism or a genetic variant in close linkage disequilibrium may interact with obesity to increase the risk of nephropathy in Chinese Type 2 diabetic patients. Apart from the need for replication of these results, functional studies are required to clarify its significance.

Keywords: chinese type 2 diabetes; diabetic nephropathy; obesity; tnf-{alpha}



   Introduction
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Tumor necrosis factor-{alpha} (TNF-{alpha}) is a multifunctional cytokine primarily produced by macrophages and adipocytes. TNF-{alpha} can directly inhibit phosphorylation of insulin receptor substrates and reduce glucose uptake by peripheral tissues. Several studies have shown that the level of expression of TNF-{alpha} correlated with obesity and hyperinsulinaemia [1], suggesting that it may be the link between obesity and insulin resistance. The G-308A polymorphism in the promoter region of the TNF-{alpha} gene had been reported to be associated with obesity, hyperleptinaemia, insulin resistance [2] and increased transcriptional activity of TNF-{alpha} [3]. However, these findings are not always reproducible in other study populations [4].

Dyslipidaemia, central obesity and insulin resistance have been reported to be associated with albuminuria in Chinese type 2 diabetic patients [5]. Given the potential effects of TNF-{alpha} on glucose and insulin metabolism, we hypothesized that G-308A polymorphism in the promoter region of the TNF-{alpha} gene might interact with obesity and affect the risk of developing diabetic nephropathy.



   Methods
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Patient population
The Prince of Wales Hospital (PWH) is the teaching hospital of the Chinese University of Hong Kong (CUHK). It serves a population of over 1.2 million. Since 1995, as part of a continuous quality improvement programme, all newly referred patients to the Clinic underwent a comprehensive assessment of complications and risk factors using standard methodology to establish the CUHK/PWH Diabetes Registry. All patients attended the unit after at least 8 h of fasting and without taking medications. Clinical assessments included the measurement of body mass index (BMI), waist–hip ratio (WHR), blood pressure as well as documentation of visual acuity and examination by fundoscopy through dilated pupils by either ophthalmologists or trained medical personnel. Diabetic retinopathy was defined as typical changes in the retina including retinal haemorrhages, exudates, neovascularization and laser scars, and a history of vitrectomy. Monofilament and a graduated tuning fork were used to assess sensory neuropathy and if foot pulses were not readily palpable, ultrasound Doppler scan was used to determine the ankle brachial ratio (ABR). Using the Asian criteria, general obesity was defined as BMI ≥25 kg/m2. Peripheral vascular disease was considered to be present if foot pulses were absent and ABR <0.9. Cardiovascular complications included a history of ischaemic heart disease, cerebrovascular disease, heart failure, myocardial infarction, revascularization and/or peripheral vascular disease. Microvascular complications were defined as the presence of retinopathy and/or sensory neuropathy.

Albuminuria was assessed using both a random spot urine sample and timed urinary collections (4 h or 24 h) after exclusion of infection using midstream urine. None of the patients had microscopic haematuria or known history of obstructive uropathy such as renal stone on ultrasound scan. Fasting blood samples were taken for measurement of plasma glucose, glycated haemoglobin (HbA1c), lipids (total cholesterol, HDL-C and triglycerides, calculated LDL-C), renal and liver functions. Albumin excretion rate (AER) was estimated from the timed urinary collection while the mean value of albumin creatinine ratio (ACR) from both samples was used to define albuminuric status. Normoalbuminuria was defined as a mean ACR ≤3.5 mg/mmol and microalbuminuria as ACR between 3.5 and 25 mg/mmol in patients with serum creatinine <150 µmol/l. Diabetic nephropathy was defined as macroalbuminuria (ACR ≥25 mg/mmol) [6] and/or serum creatinine ≥150 µmol/l. The procedures related to the study were approved by the Clinical Research Ethics Committee of the Chinese University of Hong Kong. Informed consent was obtained from all participants.

A consecutive cohort of 1281 Chinese type 2 diabetic patients who underwent detailed assessments using the above protocol between 1994 and 1998 were selected from the Registry after excluding patients with type 1 presentation, defined as diabetic ketoacidosis, acute presentation with heavy ketonuria (>3+) or continuous requirement of insulin within 1 year of diagnosis [7]. Diabetic patients with clinically identifiable secondary causes including drug-induced diabetes, pancreatic diseases and other endocrine disorders were also excluded.

Laboratory assays
Plasma glucose was measured by a hexokinase method (Hitachi 911 automated analyzer, Boerhringer Mannheim, Mannheim, Germany). HbA1c was measured by an automated ion exchange chromatographic method (Bio-Rad Laboratory, Hercules, CA, USA with reference range: 5.1–6.4%). Inter-assay and intra-assay CV for HbA1c was ≤3.1% at values below 6.5%. Total cholesterol, triglycerides (TG) and HDL-C were measured by enzymatic methods on a Hitachi 911 automated analyser (Boehringer Mannheim, Mannheim, Germany) using reagent kits supplied by the manufacturer of the analyser. Low-density lipoprotein cholesterol (LDL-C) was calculated by the Friedewald's equation for TG <4.5 mmol/l. [8]. The precision performance of these assays was within the manufacturer's specifications. Urinary creatinine (Jaffe's kinetic method) and albumin (immunoturbidimetry method) were also measured on the Hitachi 911 analyser using reagent kits supplied by the manufacturer. The inter-assay precision CV was 12.0% and 2.3% for urinary albumin concentrations of 8.0 mg/l and 68.8 mg/l, respectively. The lowest detection limit was 3.0 mg/l. Serum creatinine (Jaffe's kinetic method) was measured on a Dimension AR system (Dade Behring, Deerfield, IL, USA).

Genetic analysis
Genomic DNA was extracted from peripheral blood leukocytes. Genotyping for the TNF{alpha}-G-308A polymorphism was performed using a polymerase chain reaction–restriction fragment length polymorphism method as described by Wilson et al. [9]. A 107 bp fragment corresponded to A allele (restriction site absent) and a set of 87 bp and 20 bp fragments corresponded to G allele (restriction site present) after digestion with NcoI.

Statistical analysis
The Statistical Package for Social Sciences (Version 9.0, SPSS Inc., Chicago) was used for statistical analysis with logarithmic transformation of skewed data including TG, serum creatinine, ACR and AER. Continuous variables are expressed as mean±SD or median (interquartile range) where appropriate. Between-group comparisons were analysed using independent sample t-test, analysis of covariance and correlation coefficient (r) where appropriate. The chi-square test was used to analyse the frequencies of allele and genotype as well as that of diabetic complications. Logistic regression analysis was used to identify independent risk factors for nephropathy expressed in odds ratio (OR) and 95% confidence intervals (CI). The interaction between TNF genotype and obesity was analysed with non-obese GA/AA carriers as the reference group. Obese patients with or without GG genotype and non-obese subjects with GG genotype were independently assessed using the logistic regression analysis model after controlling for potential confounding variables. A p-value of <0.05 (two-tailed) was considered to be significant.



   Results
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
A total of 1,281 patients (41.6% male, mean age 61.0±12.0 years) were enrolled for the analysis. Of these, 369 patients had significant diabetic nephropathy. One patient in the diabetic nephropathy group had normoalbuminuria despite an elevated serum creatinine level and was excluded from analysis. Another 24 patients in the normoalbuminuric group were treated with ACE inhibitors or AII receptor antagonists at the time of urinary collection, which might confound the definition of albuminuric status. Hence 1237 patients with complete data on genotype and treatment were enrolled for final analysis. After adjustment for age and gender, patients with nephropathy were more obese, hypertensive and had worse glycaemic and lipid profiles as well as a higher percentage of cardiovascular and microvascular complications than those without nephropathy. The usage of antihypertensive drugs including ACE inhibitors and lipid-lowering drugs were similar between GG and GA/AA carriers in both obese and non-obese subjects (Tables 1 and 2). Using BMI to define obesity, there were more non-obese subjects amongst those with cardiovascular complications than those without (Table 2). Despite their lower BMI (24.2±3.4 vs 24.9±3.8, p = 0.03), these subjects had higher WHR (0.90±0.06 vs 0.89±0.07, p = 0.01) than those without cardiovascular complications.


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Table 1. Clinical and biochemical characteristics of Chinese type 2 diabetic patients divided according to their albuminuric status

 

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Table 2. Comparisons of clinical and biochemical parameters according to presence or absence of obesity and TNF G-308A genotype in 1237 Chinese type 2 diabetic patients

 
The frequency of the G allele was 91.3% and 8.7% for the A allele with observed genotype frequencies of 83.4%, 15.7% and 0.8% for GG, GA and AA, respectively. Genotype frequencies were in Hardy–Weinberg equilibrium. Carriers of GG and GA/AA genotypes had comparable age and duration of diabetes as well as similar clinical and biochemical characteristics. In the entire cohort, there was a close correlation between ACR and AER with r = 0.75 (p<0.001). As shown in Table 2, obese GG carriers (n = 449) had higher ACR and AER, lower HDL-C and were more likely to have cardiovascular complications than GA/AA carriers (n = 86). However, this difference in albuminuria was not observed in the non-obese subjects.

Using age, duration of disease, BMI, waist circumference, HbA1c, fasting plasma glucose, lipid parameters and presence of cardiovascular and microvascular complications (defined as retinopathy and/or sensory neuropathy) as independent variables, we examined the interaction of obesity and TNF-{alpha} G-308A polymorphism using non-obese GA/AA carriers as the reference group, both before and after excluding normoalbuminuric subjects with high serum creatinine or treated with ACE inhibitors or AII receptor blockers (Tables 3 and 4). In addition to male sex, systolic blood pressure, log-transformed TG and presence of cardiovascular and microvascular complications, obese subjects with the GG genotype had 2.5-fold increased risk (95% CI: 1.04–6.03; P = 0.04) of nephropathy (Table 3).


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Table 3. Multiple logistic regression analysis to examine the independent variables associated with nephropathy in 1281 Chinese type 2 diabetic patients

 

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Table 4. Multiple logistic regression analysis to examine the independent variables associated with nephropathy in 1237 Chinese type 2 diabetic patients after excluding one normoalbuminuric patient with high serum creatinine and 24 patients treated with ACE/ARB

 


   Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Although TNF-{alpha} G-308A polymorphism has been reported to be associated with obesity and insulin resistance [10,11], there were also negative reports [4] including those from Japan [12] and China [13]. In our study, we were also unable to confirm the association between G-308A polymorphism and obesity. In Caucasian populations, the frequency of the A allele was reported to be 15.8% in Sweden (n = 581) [14] and 24.2% in Northern Ireland (n = 372) [11]. By contrast, in a Chinese cohort (n = 604), the A allele frequency was only 8.7% in diabetic and 7.4% in non-diabetic subjects [15]. Similarly, in the Japanese population, the A allele frequency was only 1.4% in diabetic (n = 71) and 1.5% in non-diabetic men (n = 299) [12].

In agreement with previous studies [16], patients with nephropathy in our study were more obese, hypertensive and had a more adverse lipid and glycaemic profile than patients without nephropathy. Of note was the higher WHR but lower BMI amongst patients with cardiovascular complications than those without, thus highlighting the more important role of central obesity in cardiovascular risk. Besides, we observed that only obese GG genotype carriers had higher albuminuria than GA/AA carriers. After adjustment for potential confounding factors, obese subjects with the GG genotype had a 2.5-fold increased risk of nephropathy compared with non-obese GA/AA carriers. These results remained similar after excluding normoalbuminuric patients with high serum creatinine or those who were treated with ACE inhibitors or ARB. In support of our findings, differential effects of TNF-{alpha} gene polymorphism on glucose and lipid metabolism have been observed between obese and non-obese Finnish subjects [17].

It is now firmly established that cytokines secreted by adipocytes such as TNF-{alpha}, TNF-ß, interleukin-1{alpha}, interleukin-6 and interferon {gamma} can interact to increase insulin resistance [1]. Notably, TNF-{alpha} can cause insulin resistance by stimulating lipolysis and interfering with the activation of insulin receptor substrate and subsequent translocation of the glucose transporter. In obese subjects, TNF-{alpha} has been shown to enhance the expression of plasminogen activator inhibitor-1 and transforming growth factor-ß (TGF-ß) [18], both of which have been implicated in the pathogenesis of diabetic nephropathy [19]. Hence, it is plausible that TNF-{alpha} might interact with obesity to increase the risk of diabetic nephropathy through insulin resistance and/or interactions with other cytokines and growth factors.

Despite the reported association between AA genotype and increased TNF-{alpha} expression [3], we observed a paradoxical association between GG genotype and nephropathy in our cohort. In this regard, the association between the A allele of TNF-{alpha} gene polymorphism and insulin resistance or obesity has not been replicated in Chinese and Japanese populations and the functional significance of this polymorphism remains to be established [12,13,15]. Besides, in these two Asian populations, the frequency of the A allele was relatively low, thus raising the possibility of a survival bias although prospective studies are needed to test this hypothesis. Finally, it remains plausible that the interaction between the GG genotype and obesity might result from other unobserved functional gene polymorphisms in close linkage disequilibrium with the TNF-{alpha} G-308A polymorphism. In this connection, an association between the B9 allele of the AC/GT dinucleotide repeat polymorphism of the TNF-{alpha} gene and diabetic retinopathy had been reported in a Southern Indian population [20].

Given the plausible functions and common genetic variants of TNF-{alpha}, our findings highlight the potential interactions between obesity and cytokines such as TNF-{alpha} in the development of diabetic nephropathy. While these findings require replication in other populations, further studies are needed to examine the structure and function of this gene in different ethnic groups as well as their interactions with other genetic and environmental factors in disease development.



   Acknowledgments
 
This study was supported by a CUHK Strategic Grant, Hong Kong Research Grant Committee Earmarked Grants, Hong Kong Innovation and Technology Fund (Grant: ITS/033/00) and the Hong Kong Foundation for Research and Development in Diabetes.We thank Mr Kevin HM Yu for managing the Diabetes Database. Special thanks are extended to all staff at the Prince of Wales Hospital Diabetes and Endocrine Centre for recruiting and managing these patients. We are indebted to all patients and volunteers who have kindly donated their DNA for these genetic studies.

Conflict of interest statement. None declared.



   References
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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Received for publication: 21.12.04
Accepted in revised form: 2. 8.05





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