ABSTRACT: Background: Transforming growth factor beta1 (TGF-ß1) plays an important role in tissue fibrosis and has been found to participate in cardiovascular disease (CVD). This study aimed to evaluate the association of TGF-ß1 polymorphisms with chronic renal disease (CRD), and its progression to dialysis in a retrospective longitudinal study of an end-stage renal disease (ESRD) cohort.
Methods: The Arg/Pro (codon 25) and Leu/Pro (codon 10) polymorphisms were genotyped in 104 ESRD patients aged 64 ± 14 yrs (mean ± SD), 62 males, and in 104 matched controls.
Results: The genotype distribution of Leu10Pro and Arg25Pro polymorphisms was different between patients and controls: Leu/Leu, Leu/Pro, Pro/Pro: 0.35, 0.50, 0.15 vs. 0.30, 0.24, 0.46 (p=0.001) and Arg/Arg, Arg/Pro, Pro/Pro: 0.79, 0.21, 0 vs. 0.87, 0.10, 0.03 (p=0.019). Similarly, haplotypes constructed with the combination of both polymorphisms were different among groups. There were no differences in CRD progression rate among genotypes. Codon 10 Leu allele was associated with the presence of clinical CVD in the ESRD patients (Leu/Leu, Leu/Pro, Pro/Pro: with CVD 0.49, 0.49, 0.02 vs. without CVD 0.27, 0.51, 0.22 (p=0.01). Combined polymorphism haplotypes were also significantly different between ESRD patients with and without CVD. This association was independent from other risk factors.
Conclusions: TGF-ß1 polymorphisms are associated with ESRD, particularly in patients with associated clinical CVD, and could be useful as genetic markers of CRD and higher cardiovascular risk.

Key Words. Cardiovascular disease, Fibrosis, Genetics, Renal diseases, Transforming growth factor

Introduction

Chronic renal disease (CRD), once established, tends to progress to end-stage renal disease (ESRD). Tissue fibrosis is the histological hallmark of progressive renal disease, and is relatively independent from the primary etiology (1). On the other hand, patients with progressive CRD or ESRD have an exceedingly high risk of cardiovascular morbidity and mortality, which is not fully explained by traditional risk factors (2).
The renin-angiotensin-aldosterone system has a fund-amental role in progressive CRD development (3, 4) and possibly its complications, but recent attention has centered on downstream cytokines as potential participants and future therapeutic targets. It is known that the pro-hypertrophic actions of angiotensin II are mediated by growth factors (5). Transforming growth factor beta1 (TGF-ß1) is a multifunctional cytokine that regulates cell growth, differentiation and matrix production, inducing fibrosis in a variety of tissues such as kidney, heart and blood vessels (6). Specifically, TGF-ß1 overproduction has been linked to target organ damage in hypertension (7), and TGF-b1 gene transfer in the mesangium of normal rats leads to glomerulosclerosis (8). In human disease, increased TGF-ß production has been described in nephropathies such as glomerulonephritis, diabetic nephropathy, nephroangiosclerosis and allograft nephropathy (9). The production and secretion of TGF-ß1 in humans seem to be, in part, genetically regulated (10). Eight TGF-ß1 polymorphisms have recently been reported, the (Leu 10→Pro and Arg 25→Pro) being the most frequently studied for their association to disease and to the rate of cytokine production (11-14). Associations between TGF-ß1 gene polymorphisms and cardiovascular disease (CVD) such as myocardial infarction, diabetic nephropathy, hypertension and serum TGF-ß1 levels (11, 13-15) have been described.
This study aimed to analyze the association of the Leu 10→Pro and Arg 25→Pro TGF-ß1 polymorphisms with advanced CRD, CRD progression rate, and with the clinical characteristics and cardiovascular risk factors of this high-risk population.


Subjects and methods

Patients and clinical data

We studied 104 Caucasian ESRD patients on hemodialysis (HD) from the Division of Nephrology (Hospital Clinic, Nephrology Service, University of Barcelona), and 104 Caucasian controls. Clinical information and biochemical parameters were retrieved retrospectively from hospital records. Patients were selected with at least four serum creatinine (Cr) measurements spanning a minimum 1 yr of follow-up before HD start to calculate the slope of reciprocal Cr vs. time (1). Risk factors for CVD and for CRD progression at the time of renal insufficiency diagnosis were recorded: age, sex, present or past cigarette smoking, hypertension (blood pressure (BP) ≥140 or 90 mmHg), diabetes mellitus (fasting blood glucose ≥126 mg/dL), and dyslipidemia (serum total cholesterol >240 mg/dL and/or serum triglycerides >200 mg/dL). Clinical CVD was defined as the presence of at least one episode of the following (1) cerebrovascular accident documented by CT scan, (2) coronary artery disease defined as anginal episodes or myocardial infarction based on ECG changes, serum enzymes or angiography and; (3) peripheric vasculopathy defined by intermittent claudication or occlusive disease documented by angiography. The ethical committee of the Hospital Clinic approved the study. Consent was obtained from all patients for inclusion in the study. As a control group, 104 subjects from the same hospital admitted for elective surgery were selected with the following inclusion criteria: (1) age between 25 and 85 yrs, (2) absence of nephropathy or renal failure, diabetes mellitus or CVD.

Molecular studies

Genomic DNA was isolated from peripheral-blood lymphocytes by the standard salting-out procedure (16). The Leu 10→Pro polymorphism (a T→C transition at codon 10) and the Arg 25→Pro polymorphism (a G→C transversion at codon 25) of the TGF-ß1 gene were genotyped with flanking primers and restriction digestion (MspA1 and FseI, respectively), as described previously (16).

Statistical analysis

Results are reported as mean ± SD for normally distributed continuous variables, median (range) for non normal variables or as frequencies for categorical variables. Differences between genotype groups were analyzed using the analysis of variance (ANOVA) test followed by the Bonferroni multiple comparison or by the χ² test when appropriate. Hardy-Weinberg equilibrium was tested for each polymorphic site by the χ² test. Linkage disequilibrium between the two TGF-ß1 polymorphisms analyzed was evaluated using EH software (17). Haplotype estimations from the population genotype data were performed using PHASE version 2.0 software (18). This program was also used to perform a case-control permutation test for significant differences in haplotype frequencies in patient and control groups: ESRD vs. controls, ESRD with CVD vs. ESRD without CVD. Logistic regression analysis was performed to identify the factors independently associated with cardiovascular complications in CRD patients. Variables were included when a value p<0.3 was obtained in univariate analysis with CVD as a dependent variable and clinical and biochemical variables as independent variables. CRD progression to dialysis was evaluated in each patient as renal function loss by the slope of 1/Cr vs. time. As the distribution of the slopes was skewed, log transformation, ln (-1x1/Cr), were applied to yield more normally distributed data. Statistical tests were two-tailed, and p<0.05 was used to identify statistically significant results. Computer analyzes were done using SSPS-PC software version 11 (SPSS Inc).

Results

The ESRD patients included 104 Caucasians, 62 males and 42 females aged 64 ± 14 yrs (range 25-89 yrs) with systolic blood pressure (SBP) of 157 ± 20 mmHg and diastolic blood pressure (DBP) of 87 ± 9 mmHg and a plasma Cr at presentation of 2.6 ± 1.1 mg/dL. The
median follow-up period was 51.6 months (range 12-244). The etiology categories for CRD were nephro-angiosclerosis (n=35), diabetes mellitus (n=21), specified and unspecified glomerulonephritis (n=16),
autosomal-dominant polycystic kidney disease (n=10), interstitial nephritis (n=5) and undetermined cause (n=19). Clinical CVD was present in 37 patients; cerebrovascular disease (n=10), ischemic heart disease (n=24) and peripheric vascular disease (n=14). A control group consisted of 104 Caucasians; 58 males and 46 females aged 60 ± 13 yrs with a mean SPB and mean DBP of 117 ± 11 and 69 ± 7 mmHg, respectively. There were no significant differences in age or gender distribution between patients and controls.

DISTRIBUTION OF GENOTYPES AMONG PATIENTS AND CONTROLS
	TABLE I

The frequencies of the different genotypes studied did not deviate from the Hardy-Weinberg equilibrium in patients and in controls except for Leu10Pro in controls. As shown in Table I, the genotype distribution between ESRD patients and controls was different for both the Arg25Pro polymorphism and the Leu10Pro polymorphism. When haplotypes combining both sites were constructed, the Leu10+Arg25 haplotype was shown to be overrepresented in the ESRD group when compared to controls (p=0.001) (Tab. II) by using the permutation test (PHASE version 2.0). Similarly, there was a significant difference in haplotype distribution among patients and controls when using the χ² test (χ²=32.46, 6 d.f., p<0.001). The two polymorphisms were not in linkage disequilibrium in the ESRD patients, the controls or the complete sample set, indicating that the variants appeared to be randomly associated.

DISTRIBUTION OF RECONSTRUCTED HAPLOTYPES OF THE LEU10PRO AND ARG25PRO TGF-b1 POLYMORPHISMS IN ESRD CASES, HEALTHY CONTROLS, ESRD CASES WITH CVD AND ESRD CASES WITHOUT CVD
	TABLE II

CLINICAL AND BIOCHEMICAL CHARACTERISTICS OF THE PATIENTS AMONG GENOTYPES OF TGF-b1 CODON 10 AND CODON 25 POLYMORPHISMS
	TABLE III

Table III reports the clinical characteristics of the patients regarding the TGF-ß1 polymorphism genotypes. There were no differences in age, gender, BP, smoking status, dyslipidemia or diabetes among genotypes. The relationship between the TGF-ß1 polymorphisms and CRD progression rate was analyzed and, as shown in Table III, no differences were found. Regarding the clinical covariates, the Leu allele of codon 10 polymorphism was significantly associated with the presence of clinical CVD. Haplotype analysis showed that the Leu10+Arg25 combination was overrepresented in ESRD patients with CVD when compared to ESRD patients without CVD (p=0.011) (Tab. II) by using the permutation test. The χ² test confirmed these results (χ²=11.88, 5 d.f., p=0.036).

CLINICAL CHARACTERISTICS OF THE ESRD PATIENTS ACCORDING TO THE PRESENCE OR ABSENCE OF CLINICAL CVD
	TABLE IV

Table IV shows the univariate analysis of CVD risk fact-ors as independent variables and the presence or absence of CVD as dependent variables. In addition to codon 10 polymorphism, age, dyslipidemia and diabetes were associated with clinical CVD in the ESRD patients. A logistic regression analysis indicated that the association between the codon 10 polymorphism and clinical CVD was independent. Indeed, only dyslipidemia (p=0.010), diabetes (p=0.027) and codon 10 polymorphism (p=0.039) entered the logistic regression model as independent predictors of CVD in ESRD patients (Tab. V).

POINTWISE AND 95% CONFIDENCE INTERVAL ESTIMATES OF THE REGRESSION COEFFICIENTS FOR THE LOGISTIC REGRESSION MODEL
	TABLE V

Discussion

We analyzed the association of two TGF-ß1 polymorphisms with ESRD and CRD progression. We observed an association between the Arg25Pro and Leu10Pro polymorphisms with CRD. This association was also significant when haplotypes combining both sites were constructed (Leu10+Arg25 haplotype). It is important to note that the two polymorphisms were not in linkage disequilibrium in the ESRD group, the controls or the complete sample set; therefore, indicating that the variants appeared to be randomly associated and supplied independent information.
In addition, the Leu10Pro polymorphism was significantly and independently associated with the presence of CVD in the ESRD patients studied. Similarly, haplotype analysis showed that the Leu10+Arg25 combination was overrepresented in ESRD patients with CVD when compared to ESRD patients without CVD.
Variants of the TGF-ß1 gene have previously been associated with differences in the production, secretion or activity of this cytokine (13). Through several mechanisms, the variable availability of this growth factor in different tissues could affect endothelial function (19, 20) and influence BP, interfere with the development of atherosclerosis (21), and influence vascular (22-24) and cardiac (25) remodeling.
The independent association between the Leu10Pro polymorphism and the presence of clinical CVD in ESRD patients could be clinically important indicating its potential use as a genetic marker for higher cardiovascular risk in ESRD patients. It is known that ESRD patients have a very high risk of CVD, which is not fully explained by the presence or accumulation of traditional risk factors (2). TGF-ß1 polymorphisms have been associated with myocardial infarction, hypertension and serum TGF-ß1 levels (11, 14, 26) in non-renal patients. In the ECTIM STUDY (11), the Pro25 allele was associated with an increased risk of myocardial infarction and a reduced risk of hypertension. Similarly, Li et al (14) found that the Arg25 allele was more frequent in hypertensive subjects. Recently, Yokota et al (26) described an association between the Leu10 allele and susceptibility to myocardial infarction in males with conventional cardiovascular risk factors. In agreement with the latter study, we observed an association between clinical CVD and the Leu10 allele. The important difference is that this association was also present in CRD patients, this study being the first to explore this issue in this type of high-risk CVD patients. Serum TGF-ß levels were not measured in this retrospective study. It is known that present serum TGF-ß levels would not be useful as predictor variables or for pathogenic associations, since these levels are influenced by disease status (26).
Finally, concerning CRD and progression, we found that TGF-ß1 gene variants did not influence the progression rate. This is controversial since Pociot et al (15) found a weak but significant association of the Thr263Ile variant with diabetic nephropathy, whereas Akai et al (27) did not find an association between the codon 10 Leu/Leu genotype and faster progression in this disease. Recent work has shown a correlation
between the TGF-ß1 Leu10 allele and more severe histological renal damage and with progressive renal function deterioration in IgA nephropathy (28, 29). The finding that allele Leu10 was more frequent in ESRD patients than in controls correlates with the results observed by other studies (29) and is consistent with the idea that TGF-ß could participate as a key factor in the common mechanisms leading to tissue fibrosis and the development of advanced CRD of various etiologies.
In conclusion, TGF-ß1 polymorphisms are associated with CRD and could be markers for higher cardiovascular risk in this population. Tissue and vascular growth and fibrosis are common mechanisms for the development of renal and cardiovascular disease and these results suggest that TGF-ß1 gene variants could play a role in both processes. However, due to the common problems concerning the lack of reproducibility of genetic association studies, probably resulting from a mix of type 2 errors, sample stratifications and inadequate sample size (30), larger and prospective studies are necessary to confirm these results.


Acknowledgements

This work was supported in part by a grant from the Fondo de Investigaciones Sanitarias, FIS 01/1151, and a grant by the Hospital
Clinic (to E.C.).


Address for correspondence:
Esteban Poch, M.D.
Servicio de Nefrología
Hospital Clínic
Universidad de Barcelona
Villarroel 170
08036 Barcelona, Spain
epoch@medicina.ub.es

REFERENCES (when available, each reference has been linked to PubMed)

1. Klahr S, Schreiner G, Ichikawa I. The progression of renal disease. N Engl J Med 1988; 318: 1657-66.
2. Zoccali C. Cardiovascular risk in uraemic patients: is it fully explained by classical risk factors? Nephrol Dial Transplant 2000; 15: 454-7.
3. Anderson S, Meyer TW, Rennke HG, Brenner BM. Control of glomerular hypertension limits glomerular injury in rats with reduced renal mass. J Clin Invest 1985; 76: 612-9.
4. Remuzzi G, Ruggenenti P, Perico N. Chronic renal diseases: Renoprotective benefits of renin-angiotensin system inhibition. Ann Intern Med 2002; 136: 604-15.
5. Marx M, Sterzel RB, Sorokin L. Renal matrix and adhesion in injury and inflammation. Curr Opin Nephrol Hypertens 1993; 2: 527-35.
6. Border WA, Noble NA. Transforming growth factor-b in tissue fibrosis. N Engl J Med 1994; 331: 1286-92.
7. Villarreal FJ, Dillmann WH. Cardiac hypertrophy-induced changes in mRNA levels of TGF, fibronectin, and collagen. Am J Physiol 1992; 262: H1861-6.
8. Isaka Y, Fujiwara Y, Ueda N, Kaneda Y, Kamada T, Imai E. Glomerulosclerosis induced by in vivo transfection of transforming growth factor-beta or platelet-derived growth factor gene into the rat kidney. J Clin Invest 1993; 92: 2597-601.
9. Yamamoto T, Noble NA, Cohen AH, Nast CC, Hishida A, Gold LI, Border WA. Expression of TGF-beta isoforms in
human glomerular diseases. Kidney Int 1996; 49: 461-9.
10. Awad MR, El-Gamel A, Hasleton P, Turner DM, Sinnott PJ, Hutchinson IV. Genotypic variation in the transforming growth factor-b1 gene. Transplantation 1998; 66: 1014-20.
11. Cambien F, Ricard S, Troesch A, Mallet C, Generenaz L, Evans A, Arveiler D, Luc G, Ruidavets JB, Poirier O. Polymorphisms of the transforming growth factor-b1 gene in relation to myocardial infarction and blood pressure. The Etude Cas-Temoin de L’Infarctus du Myocarde (ECTIM study). Hypertension 1996; 28: 881-7.
12. Grainger DJ, Heathcote K, Chiano M, Snieder H, Kemp PR, Metcalfe JC, Carter ND, Spector TD. Genetic control of the circulating concentration of transforming growth factor type b1. Hum Mol Genet 1999; 8: 93-7.
13. El-Gamel A, Awad M, Sim E, Hasleton P, Yonan N, Egan J,
Diraniya A, Hutchinson IV. Transforming growth factor-b1 and lung allograft fibrosis. Eur J Cardiothorac Surg 1998; 13: 424-30.
14. Li B, Khanna A, Sharma V, Singh T, Suthanthiran M, August P. TGF-b1 DNA polymorphisms, protein levels, and blood pressure. Hypertension 1999; 33: 271-5.
15. Pociot F, Hansen PM, Karlsen AE, Langdahl BL, Johannesen J, Nerup J. TGF-beta1 gene mutations in insulin-dependent diabetes mellitus and diabetic nephropathy. J Am Soc Nephrol 1998; 9: 2302-7.
16. Lario S, Iñigo P, Campistol JM, Poch E, Rivera F, Oppenheimer F. Restriction enzyme-based method for transforming growth factor-b1 genotyping: nonisotopic detection of polymorphisms in codons 10 and 25 and the 5’-flanking region. Clin Chem 1999; 45: 1290-2.
17. Terwilliger J, Ott T. Handbook of human genetic linkage. Baltimore: John Hopkins University Press 1994.
18. Stephens M, Smith N, Donnelly P. A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 2001; 68: 978-89.
19. Dickson K, Philip A, Warshawsky H, O’Connor-McCourt M, Bergeron JJ. Specific binding of endocrine transforming growth factor-b1 to vascular endothelium. J Clin Invest 1995; 95: 2539-54.
20. Zeiher AM, Drexler H, Wollschlager H, Just H. Modulation of coronary vasomotor tone in humans: progressive endothelial dysfunction with different early stages of coronary athero-sclerosis. Circulation 1991; 83: 391-401.
21. Grainger DJ, Kemp PR, Metcalfe JC, Liu AC, Lawn RM, Williams NR, Grace AA, Schofield PM, Chauhan A. The serum concentration of active transforming growth factor-
beta is severely depressed in advanced atherosclerosis. Nat Med 1995; 1: 74-9.
22. Agrotis A, Saltis J, Bobik A. Transforming growth factor-b1 gene activation and growth of smooth muscle from hyper-
tensive rats. Hypertension 1994; 23: 593-9.
23. Ohno M, Cooke JP, Dzau VJ, Gibbons GH. Fluid shear stress induces endothelial TGF-b1 transcription and production: modulation by potassium channel blockade. J Clin Invest 1995; 95: 1363-9.
24. Roberts AB, Sporn MB, Assoian RK, Smith JM, Roche NS, Wakefield LM, Heine UI, Liotta LA, Falanga V, Kehrl JH. Transforming growth factor b: rapid induction of fibrosis and angiogenesis in vivo and stimulation of collagen formation
in vitro. Proc Natl Acad Sci U S A 1986; 83: 4167-71.
25. Takahashi N, Calderone A, Izzo NJ Jr, Maki TM, Marsh JD, Colucci WS. Hypertrophic stimuli induce transforming growth factor-b1 expression in rat ventricular myocytes. J Clin Invest 1994; 94: 1470-6.
26. Yokota M, Ichihara S, Lin TL, Nakashima N, Yamada Y. Association of a T29 ÆC polymorphism of the transforming growth factor-b1 gene with genetic susceptibility to myocardial infarction in Japanese. Circulation 2000; 101: 2783-7.
27. Akai Y, Sato H, Ozaki H, Iwano M, Dohi Y, Kanauchi M. Association of transforming growth factor-beta1 T29C polymorphism with the progression of diabetic nephropathy. Am J Kidney Dis 2001; 38 (suppl 1): S182-5.
28. Brezzi B, Brugnara M, Lupo A, Magistroni R, Furci L, Ligabue G, Bernich P, Turco A, Gomez-Lira M, Del Prete D, Maschio G. Genetic polymorphisms of TGF-beta1 and histological damage in IgA nephropathy. J Am Soc Nephrol 2002; 13: 131A.
29. Brezzi B, Lupo A, Brugnara M, Ligabue G, Magistroni R, Marcantoni C, Gomez-Lira M, Gambaro G, Turco A, Poli A, Maschio G. TGF-beta1 COD10 polymorphism is associated with progressive IgA nephropathy. J Am Soc Nephrol 2002; 13: 130A.
30. Colhoun HM, McKeigue PM, Smith GD. Problems of reporting genetic associations with complex outcomes. Lancet 2003; 361: 865-72.


Received: April 15, 2004
Revised: August 06, 2004
Accepted: October 11, 2004

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