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Abstract

Objective:

Although the angiotensinogen (AGT) gene T174M polymorphism has been implicated in the pathogenesis of diabetic nephropathy (DN), study results have been inconsistent. The present meta-analysis was conducted to determine the correlation of AGT T174M polymorphism with DN.

Methods:

We retrospectively extracted relevant studies from Embase as well as PubMed databases. Additionally, a fixed- or random-effects model was employed for calculation of pooled odds ratio (OR) along with 95% confidence interval (CI).

Results:

In total, we identified six studies (1179 cases and 927 controls) regarding the AGT gene T174M polymorphism. The pooled ORs for the association between the AGT T174M polymorphism and DN risk were not statistically significant under all genetic models (M vs T: OR = 1.22, 95% CI = 0.84–1.75; MM vs TT: OR = 1.94, 95% CI = 0.93–4.04; MT vs TT: OR = 1.11, 95% CI = 0.76–1.63; the dominant model: OR =1.19, 95% CI = 0.80–1.77; the recessive model: OR = 1.94, 95% CI = 0.93–4.03). Subgroup analyses based on the type of race showed the M allele of the AGT T174M polymorphism increased DN risk in Asians, but not in Caucasians.

Conclusions:

Our study indicated that the T174M polymorphism in the AGT gene was associated with DN in Asians.

Keywords

diabetic nephropathy meta-analysis polymorphism T174M

Introduction

Diabetic nephropathy (DN) is a major microvascular complication during the progression both of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), accounting for 25%–40% of DM-associated morbidity and mortality.¹ Moreover, DN is among the leading causes of end-stage renal disease in Western countries.^2,3 Therefore, earlier diagnosis and prevention of DN is important. However, the mechanism of DN is complicated. In spite of a certain correlation between DN and plasma glucose levels/diabetes duration, it is not definitely clarified. Certain DM patients with well-controlled plasma glucose levels are burdened with DN in the early course of DM, while some of the remaining do not develop DN throughout their life. Therefore, it is likely that hyperglycemia is a critical, but not the only, factor affecting DN development. Recent studies show that genetic factors are critically involved in DN development as well.^4,5

The renin-angiotensin-aldosterone system (RAAS), playing a vital part in the modulation of renal homeostasis, sodium and water balance as well as blood pressure, also participates in the pathophysiology of DN.^6,7 In other words, RAAS dysregulation is critically involved in DN pathogenesis. Excessive RAAS activation constricts renal arterioles leading to increased peripheral and renal resistance, increases glomerular capillary pressure leading to proteinuria, augments oxidative stress leading to endothelial dysfunction and so on.⁸ All these aggressively damage renal function, eventually leading to DN. Targeted inhibition of the activation of RAAS with angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers is the most common clinical strategy for slowing disease progression.⁹

Angiotensinogen (AGT) is a liver protein interacting with the protease renin to generate angiotensin I, a pro-hormone of angiotensin II. Ang II has been demonstrated to participate in cardiac fibrosis, regulation of collagen synthesis and cardiac fibroblast growth as well as progression of cardiomyocyte hypertrophy both in human and animal models. Genetic polymorphisms of AGT are likely to influence RAAS activity, subsequently affecting the pathogenesis and progression of DN. The AGT gene is located at lq42–43 and consists of five exons. A threonine to methionine substitution at amino acid 174 is a common polymorphism called T174M (rs699), designating the T and M alleles, respectively.¹⁰

Various epidemiological research has investigated the relationship of AGT T174M polymorphism with DN risk, without consistent conclusions. Meta-analysis can be a useful tool in detecting an association that could otherwise remain masked in smaller sample size studies, especially in those evaluating the frequency of rare allele polymorphisms.¹¹ Hence, the present meta-analysis aimed at exploring the correlation of the AGT T174M polymorphism with DN risk via collection of all available case-control studies.

Participants and methods

Identification of studies

The following terms were searched for in the Embase and PubMed databases: “AGT/ angiotensinogen,” “T174M,” “DN/diabetic nephropathy” and “gene polymorphism.” In addition, we also manually screened the references of retrieved researches for a comprehensive collection of eligible studies. We established a flowchart of information concerning identification, screening and eligibility and finally selected datasets in line with Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines.¹²

Inclusion criteria and data extraction

The inclusion criteria were as follows: 1) case-control research addressing DN cases and controls, 2) research assessing the correlation of AGT T174M polymorphism with DN risk, 3) research with adequate genotype information for extraction and 4) the definition of DN was urinary albumin excretion >30 mg/24 hours. Studies were excluded when: 1) articles were not case-control studies assessing the relationship of AGT T174M polymorphism with DN risk, 2) reviews, editorial articles, letters, case reports as well as meta-analysis, 3) research was based on insufficient raw data or without useful information, 4) research was duplicated and 5) sample size was less than 10.

Data extraction

Authors N.L. and Y.W. independently retrieved relevant information from all eligible searches, and consensus was reached on all items. The following data were extracted from every study: first author, year of publication, area, ethnicity, number and genotypes of cases and controls, as well as evidence of Hardy-Weinberg equilibrium (HWE) in controls.

Statistical analysis

Fisher exact test was applied to evaluate deviation from HWE for each genotype distribution in the control group. The strength of the associations between the T174M polymorphism and susceptibility to DN were estimated by odds ratio (OR) and 95% confidence interval (95% CI) under M vs T, a homozygote comparison (MM vs TT), a heterozygote comparison (MT vs TT), a dominant model (MM+MT vs TT) and a recessive mode (TT+MT vs MM) between groups. The heterogeneity among these articles was checked via the I² test. When I² > 50% indicated heterogeneity across studies, the random-effects model was used, otherwise the fixed-effects model was used. The sensitivity analysis was used by omitting each individual article, and an individual article was suspected of excessive sensitivity if the point estimate of its omitted analysis was outside the 95% CI of the pooled analysis. To assess potential publication bias, visual inspection of a Begg funnel plot was performed. STATA version 12.0 was employed for statistical analysis.

Results

Study characteristics

Through data retrieval, 281 possible relevant researches were identified that met the search criteria. After carefully screening according to the criteria, duplicated studies and review articles were excluded. There were only six studies included in the meta-analysis^13–18 comprising 1179 DN patients and 927 controls (Figure 1). Study regions were composed of Denmark, Spain, Italy and China. Participants were grouped into three ethnicities, namely African, Asian and Caucasian (Table 1). Data from the included studies for meta-analysis is included in Table 2.

Figure 1.

Flowchart of selection of studies and specific reasons for exclusion from the meta-analysis.

Table 1.

Characteristics of studies included in meta-analysis.

Study first author^ref	Year	Area	Race	DM type	Matching criteria	Cases/Controls
Tarnow¹³	1996	Denmark	Caucasian	Type 1	Age, sex, duration, BMI	195/185
Gutiérrez¹⁴	1997	Spain	Caucasian	–	Sex	193/90
Solini¹⁵	1999	Italy	Caucasian	Type 2	Age, BMI, duration, HbA_1c (%)	79/90
Wu¹⁶	2000	China	Asian	–	–	71/41
Chang¹⁷	2003	China	Asian	Type 2	Age, sex	129/116
Mtiraoui¹⁸	2011	Tunisia	African	Type 2	Age, sex, BMI	512/405

BMI: body mass index; DM: diabetes mellitus; HbA_1c: hemoglobin A_1c.

Table 2.

Data of studies included in meta-analysis.

Study first author^ref	Allele	For cases	Allele	For controls	Genotypes for cases			Genotypes for controls			HWE test
Study first author^ref	T	M	T	M	TT	TM	MM	TT	TM	MM	HWE test
Tarnow¹³	336	54	324	46	148	44	1	141	42	2	0.56
Gutiérrez¹⁴	340	46	154	26	149	40	4	67	20	3	0.33
Solini¹⁵	140	18	160	20	62	14	3	71	18	1	0.91
Wu¹⁶	125	17	77	5	58	9	4	36	5	0	0.67
Chang¹⁷	220	38	220	12	93	33	3	105	11	0	0.59
Mtiraoui¹⁸	908	116	710	100	403	99	10	311	91	3	0.19

HWE: Hardy-Weinberg equilibrium; M: methionine; T: threonine.

Pooled analyses

The evaluation of the relationship of the AGT gene T174M polymorphism with DN risk is presented in Figure 2 and Table 3. Meta-analysis results revealed no significant relationship between the AGT T174M polymorphism and DN risk (M vs T: OR = 1.22, 95% CI = 0.84–1.75; MM vs TT: OR = 1.94, 95% CI = 0.93–4.04; MT vs TT: OR = 1.11, 95% CI = 0.76–1.63; the dominant model: OR = 1.19, 95% CI = 0.80–1.77; the recessive model: OR = 1.94, 95% CI = 0.93–4.03). In subgroup analysis by ethnicity, a significant association was found between the AGT T174M polymorphism and DN risk in Asians (M vs T: OR = 2.80, 95% CI = 1.59–4.93; the dominant model: OR = 2.73, 95% CI = 1.25–5.96), but not in Caucasians. In assessment of the impact of single literature on final result, sensitivity analysis was performed by omitting studies each time in turn. As a result, elimination of a single study rarely affected the pooled results, indicating that our findings were robust (Figure 3).

Figure 2.

Meta-analysis for the association between DN risk and AGT T174M polymorphism(M vs T) as illustrated in subgroup analysis.

Table 3.

Summary of different comparative results.

Subgroup	N	OR (95% CI)
		M vs T	MM vs TT	MT vs TT	Dominant model	Recessive model
Total	6	1.22 (0.84–1.75)	1.94 (0.93–4.04)	1.11 (0.76–1.63)	1.19 (0.80–1.77)	1.94 (0.93–4.03)
Race
Caucasian	3	1.00 (0.74–1.34)	0.93 (0.32–2.72)	0.95 (0.67–1.33)	0.95 (0.68–1.32)	0.95 (0.33–2.75)
Asian	2	2.80 (1.59–4.93)	6.62 (0.81–54.04)	2.14 (0.73–6.25)	2.73 (1.25–5.96)	5.97 (0.74–48.42)

CI: confidence interval; M: methionine; N: number; OR: odds ratio; T: threonine.

Figure 3.

One-way sensitivity analysis of the pooled odds ratios and 95% confidence interval (CI) for angiotensinogen gene T174M polymorphism, omitting each dataset in the meta-analysis (M vs T).

Publication bias

A Begg funnel plot was used to evaluate whether there was publication bias for the AGT T174M polymorphism. Consequently, the shape of the funnel plot did not reveal any evidence of obvious asymmetry. The results still did not suggest any evidence of publication bias for the AGT T174M polymorphism (Figure 4).

Figure 4.

Begg funnel plot test of publication bias.

Discussion

Recent epidemiological studies indicate that the global prevalence of DM has increased to 9.1%. According to a recent report,¹⁹ the total number of adults with diabetes has increased to 415 million by 2015. DN is among the most common microvascular complications of DM. The pathogenesis of DN is complicated, and poor glycemic control and genetic susceptibility both play an important role. In a population-based case-control study, Tarnow et al.¹³ were the first to report the correlation of the AGT T174M polymorphism with DN.¹³ Their study comprised 195 individuals who survived DN and 185 DM patients with persisting normoalbuminuria, while AGT locus did not significantly affect DN risk. In contrast to the above study, several but not all later studies confirmed the association of the T174M polymorphism with increased risk for DN. Nevertheless, it is likely that the reported associations of T174M polymorphism with elevated DN risk might not actually reflect the reality based on the small sample size. To help clarify the inconsistent findings, the present meta-analysis was performed to identify the potential correlation of T174M polymorphism with DN risk by retrieving relevant research.

To our knowledge, this is the first meta-analysis to quantitatively evaluate the correlation of the AGT T174M polymorphism with DN risk. In this study, we included and assessed six case-control studies comprising 1179 DN cases as well as 927 controls. As a result, this polymorphism was insignificantly related with DN risk. In a subgroup analysis stratified by ethnicity, the M allele of the AGT T174M polymorphism was significantly correlated with DN risk in Asians, but not in Caucasians, implicating a possible role of ethnic differences in genetic backgrounds and the environment in which they live. A study by Mtiraoui and colleagues¹⁸ aimed at Africans. We cannot perform further subgroup analysis in Africans for only one study. The expression of traits is influenced not only by genotypes, but also by lifestyle, nutritional status, geographical environment, economic level, and the diabetic control group with potential complications, small sample size or lower-power value in some comparisons, all of which potentially affect the results. There have been only two studies on this locus in Asians, so further research is needed to verify our results.²⁰ Sensitivity analysis further validated that the AGT T174M polymorphism is significantly correlated with DN risk. There is no evidence of possible publication bias in the present meta-analysis.

The serum AGT level was not changed in individuals with the T174M variant.²¹ The mechanism of the relationship of AGT T174M polymorphism with DN risk remains undefined. The potential effect of the T174M polymorphism might be influenced by gene-gene interaction. The M235T polymorphism has been associated with elevated levels of AGT. AGT interacts with renin to produce angiotensin II. Ang II activates vascular cell apoptosis, contributing to vascular remodeling and hypertension,²² while hypertension is considered as the vital risk factor for DN progression.²³ A recent meta-analysis has demonstrated that the AGT M235T polymorphism could significantly enhance DN risk.²⁴ AGT M235T and T174M variants are in linkage disequilibrium, and gene-gene interaction of M235T and T174M might synergistically increase the risk of DN.

There are certain limitations in this meta-analysis. First, our systematic review was based on unadjusted data, as the genotype information stratified for the main confounding variables was not available in the original papers and the confounding factors addressed across the different studies were variable. Second, publication bias is possible because all articles included in the current meta-analysis were published in English. Finally, the effect of gene-gene and gene-environment interactions was not addressed in this meta-analysis.

In conclusion, our findings implicate a significant association of the AGT T174M polymorphism with DN risk in Asians. Large-scale case-control and population-based association studies are warranted to validate the risk identified in the current meta-analysis and investigate potential gene-gene and gene-environment interactions on DN risk.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Youmin Wang

References

Collins

Foley

Chavers

et al . US Renal Data System 2013 Annual Data Report. Am J Kidney Dis 2014; 63 (1 Suppl): A7.

Kato

Arce

Natarajan

MicroRNAs and their role in progressive kidney diseases. Clin J Am Soc Nephrol 2009; 4: 1255–1266.

Kanwar

Wada

Sun

et al . Diabetic nephropathy: Mechanisms of renal disease progression. Exp Biol Med 2008; 233: 4–11.

McDonough

Palmer

Hicks

et al . A genome-wide association study for diabetic nephropathy genes in African Americans. Kidney Int 2011; 79: 563–572.

Sandholm

Salem

McKnight

et al . New susceptibility loci associated with kidney disease in type 1 diabetes. PLoS Genet 2012; 8: e1002921.

Ruggenenti

Cravedi

Remuzzi

The RAAS in the pathogenesis and treatment of diabetic nephropathy. Nat Rev Nephrol 2010; 6: 319–330.

Sparks

Crowley

Gurley

et al . Classical renin-angiotensin system in kidney physiology. Compr Physiol 2014; 4: 1201–1228.

Roscioni

Heerspink

de Zeeuw

The effect of RAAS blockade on the progression of diabetic nephropathy. Nat Rev Nephrol 2014; 10: 77–87.

Batlle

Wysocki

Soler

et al . Angiotensin-converting enzyme 2: Enhancing the degradation of angiotensin II as a potential therapy for diabetic nephropathy. Kidney Int 2012; 81: 520–528.

10.

Sivitskaia

Kushnerevich

Danilenko

et al . Gene polymorphism of the renin-angiotensin system in six ethnic/geographic regions of Belarus [article in Russian]. Genetika 2008; 44: 702–709.

11.

Attia

Thakkinstian

D’Este

Meta-analyses of molecular association studies: Methodologic lessons for genetic epidemiology. J Clin Epidemiol 2003; 56: 297–303.

12.

Moher

Liberati

Tetzlaff

et al . Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 2009; 6: e1000097.

13.

Tarnow

Cambien

Rossing

et al . Angiotensinogen gene polymorphisms in IDDM patients with diabetic nephropathy. Diabetes 1996; 45: 367–369.

14.

Gutiérrez

Vendrell

Pastor

et al . Angiotensin I-converting enzyme and angiotensinogen gene polymorphisms in non-insulin-dependent diabetes mellitus. Lack of relationship with diabetic nephropathy and retinopathy in a Caucasian Mediterranean population. Metabolism 1997; 46: 976–980.

15.

Solini

Giacchetti

Sfriso

et al . Polymorphisms of angiotensin-converting enzyme and angiotensinogen genes in type 2 diabetic sibships in relation to albumin excretion rate. Am J Kidney Dis 1999; 34: 1002–1009.

16.

Xiang

Zheng

et al . Relationship between the renin-angiotensin system genes and diabetic nephropathy in the Chinese. Chin Med J (Engl) 2000; 113: 437–441.

17.

Chang

Cheng

Shu

et al . Study of the polymorphism of angiotensinogen, angiotensin-converting enzyme and angiotensin receptor in type II diabetes with end-stage renal disease in Taiwan. J Chin Med Assoc 2003; 66: 51–56.

18.

Mtiraoui

Ezzidi

Turki

et al . Renin-angiotensin-aldosterone system genotypes and haplotypes affect the susceptibility to nephropathy in type 2 diabetes patients. J Renin Angiotensin Aldosterone Syst 2011; 12: 572–580.

19.

Fan

Cai

Chen

et al . Association of the transcription factor 7 like 2 (TCF7L2) polymorphism with diabetic nephropathy risk: A meta-analysis. Medicine (Baltimore) 2016; 95: e3087.

20.

Qiao

Wang

Pan

et al . The relationship between ACE/AGT gene polymorphisms and the risk of diabetic retinopathy in Chinese patients with type 2 diabetes. J Renin Angiotensin Aldosterone Syst 2018; 19: 1470320317752955.

21.

Pilbrow

Palmer

Frampton

et al . Angiotensinogen M235T and T174M gene polymorphisms in combination doubles the risk of mortality in heart failure. Hypertension 2007; 49: 322–327.

22.

Jeunemaitre

Soubrier

Kotelevtsev

et al . Molecular basis of human hypertension: Role of angiotensinogen. Cell 1992; 71: 169–180.

23.

Chowdhury

Dronsfield

Kumar

et al . Examination of two genetic polymorphisms within renin-angiotensin system: No evidence for an association with nephropathy in IDDM. Diabetologia 1996; 39: 1108–1114.

24.

Zhou

Wen

et al . Associations between angiotensinogen M235T polymorphisms and the risk of diabetic nephropathy: A meta-analysis. Diabetes Res Clin Pract 2018; 142: 26–36.

Association between angiotensinogen T174M polymorphism and the risk of diabetic nephropathy: A meta-analysis