Significant Correlation Between Association of Polymorphism in Codon 10 of Transforming Growth Factor-β1 T (29) C With Type 1 Diabetes and Patients With Nephropathy Disorder

Abstract

Type 1 diabetes is an autoimmune disease that is caused by destruction of pancreatic β-cells. Type 1 diabetes is a heterogenic disease with environmental factors as well as genetic components. It is well established that environmental factors can exert their effects only on genetically susceptible patients. There is increasing evidence that genes outside the major histocompatibility complex (MHC) region contribute to the pathogenesis of type 1 diabetes. Cytokines, due to their role in immune regulation, seem to play a crucial role in the pathogenesis of the disease. In order to investigate the immunosuppressive action of transforming growth factor-β1 (TGF-β1) in type 1 diabetes, 388 patients with type 1 diabetes and 229 normal controls were genotyped for the TGF-β1 T (29) C gene polymorphism. The TGF-β1 T (29) C gene polymorphism was amplified using ARMS-PCR. Practical part of this work was conducted in Molecular Medicine Research Group, Peninsula Medical School, Plymouth, UK. However, statistical analyses were performed in Department of pathology, Salmaniya Medical Complex, Kingdom of Bahrain. From three different genotypes of TT, TC, and CC of the TGF-β1 T (29) C, the TC frequency increased in patients with type 1 diabetes compared to normal controls, P value = 0.00001. The TC frequency was significantly higher in patients with diabetic nephropathy (DN) in comparison with diabetic control, P value = 0.007. Further, the CC frequency was significantly less in patients compared to healthy normal control subjects, P value = 0.005. Genetic variation at the TGF-β1 gene polymorphism T (29) C located in codon 10 is likely to confer significant susceptibility to advanced DN in patients with T1D. This is a small case–control study in Caucasians to investigate the role of the TGF-β1 gene polymorphism T (29) C located in codon 10 in the genetic predisposition to T1D and DN. To our knowledge, this is the first genetic report highlighting the dual effects of TGF-β1 in the onset of T1D as well as type 1 DN and can be a good model for extensive studies.

Introduction

Type 1 diabetes (T1D) is an autoimmune disease that is caused as a result of destruction of pancreatic β-cells. Several factors may contribute to the pathogenesis of T1D. Genetic susceptibility of T1D is determined by polymorphisms/mutations in multiple genes in both human and animal models. This includes rare immunologic syndromes, such as the autoimmune polyendocrine syndrome type 1 (APS-1), and the immune dysfunction enteropathy, X-linked (IPEX) syndrome, in which mutations of single genes greatly enhance the risk of developing autoimmune diabetes (Wildin and others 2001; Halonen and others 2002; Wildin and others 2002; Jahromi and Eisenbarth 2007). Majority of individuals born with mutations of the FOXP3 gene (IPEX syndrome) develop diabetes as neonates or young infants, indicating that, in the absence of FOXP3-dependent function (most likely because of the lack of a major class of regulatory T cells), there is high risk for immune destruction of islet β cells (Wildin and others 2002).

The major histocompatibility complex (MHC) accounts for ∼50% of the familial aggregation of T1D and the insulin gene for only 10% (Wildin and others 2001; Halonen and others 2002; Wildin and others 2002; Concannon and others 2005; Jahromi and Eisenbarth 2007) suggesting the existence of additional loci. The gene for PTPN22, the lymphocyte-signaling molecule, on chromosome 1p13.3–p13.1 is a confirmed locus that contributes to multiple autoimmune disorders, including T1D (Begovich and others 2004). Diabetes-associated CTLA-4 locus polymorphisms in most populations have relative risks <1.5 (Marron and others 2000). A fundamental question is whether there are genetic polymorphisms that confer major risk for T1D, other than the HLA DR and DQ alleles (class II HLA alleles). Recently, genes outside MHC region have considered playing an important role in the onset of diabetes.

To date there are 983 positional candidate genes from the 18 established linkage with T1D (compiled from T1Dbase (http://t1dbase.org)). Interestingly accumulative reports suggest that interacting proteins often share similar function, and participate in the same biological pathways and processes (Oti and others 2006). Therefore, polymorphism/mutations in genes coding for them could lead to similar disease phenotypes. These facts indicated that protein–protein interaction (PPI) information alone may offer a simple, efficient means to prioritize candidate genes (Oti and others 2006). Recently, Geo and others in a clever approach to PPI have reached to three genes that each interacts with five known T1D genes: SMAD2, RELA, and DAXX (Gao and Wang 2009). SMAD2 modulates the signal for transforming growth factor-β1 (TGF-β1) and thus regulates multiple cellular processes, such as differentiation, proliferation, and apoptosis. TGF-β1 plays a central role in activation of inflammation; and in the regulation of anti-islet CD8+T cells by CD4+CD25+T regulatory cells during T1D (Smart and others 2006). RELA is known as p65. Its protein is involved in protection of target cells against apoptosis by a variety of death effectors, including cytokine-mediated β-cell death (Chang and others 2003). DAXX, death-associated protein 6, is in the MHC-extended region. It is involved in the T1D disease pathways in patients displaying intermediate risk DQ–DR haplotypes (van der Slik and others 2007). It modulates TGF-β apoptotic signaling pathway by binding to the receptor TGF-β (Perlman and others 2001). It physically interacts with GLLUT4 as well (Lalioti and others 2002).

Search for a genetic marker that increases the risk of diabetic nephropathy (DN) is important. However, there is a little known about genetic of DN due to late appearing onset of DN. No mutations in genes have been identified association implicate with regard to the disease (Linder and others 2003). Case–control study is a difficult task to be carried in a center due to rarity of the cases and controls and a multicenter effort is required. Recently, however, there are two interesting studies investigating the TGF-β1 gene polymorphisms in particular the T (29) C polymorphism in DN (Ng and others 2003; Patel and others 2005).

Further, there is a large body of evidence of genetic predisposition to DN comes from familial studies of The Diabetes Control and Complications Trial Research Group (1997). Initial familial genetic predisposition studies in patients with T1D showed that in families with two or more T1D siblings when one sibling developed DN the other was at fourfold risk of DN compared to sibling of a patient of T1D without DN (Seaquist and others 1989; Borch-Johnsen and others 1992). Quinn and others have evaluated these findings in a much larger analysis. They reported the sibling of a patient with DN has a cumulative risk of DN about 71.5%. This risk fell to 25.4% where the proband did not have DN (Quinn and others 1996).

Cytokines that act as mediators of immune responses are classified into different groups. T helper (Th)1 cytokines, usually termed proinflammatory, are involved in the regulation of cell-mediated immune responses and play a leading role in the onset of T1D (Huang and others 1995; Berman and others 1996; Faust and others 1996; Jahromi and others 2000a). Th2 cytokines are involved in the control of antibody production, in disease remission, and the suppression of immune responses. In healthy normal condition, Th1 and Th2 cytokines are in cross-regulation phase (Th1/Th2), that is these cells are mutually suppressive (Maggi and others 1992; Marselli and others 2001; You and others 2006). Evidence obtained from working within these models suggests that manipulating the Th1/Th2 balance in the immune response can alter disease processes (You and others 2006). The progression to overt diabetes resulting in a significant β-cell destruction is triggered by the development of a more aggressive T-cell phenotype and a change in the Th1/Th2 balance toward a more proinflammatory milieu (Th1-dominant) (You and others 2006). Furthermore, increasing evidence demonstrating the association of the Th17 subset, the recently discovered CD4+ effector T-cell lineage distinct from Th1 and Th2, with pathogenesis of T1D (You and others 2006; Kurts 2007).

TGF-β1 is immunosuppressive and plays a role in the resolution of inflammatory responses in a large variety of organ-specific autoimmune diseases (Yamada and others 1998, 1999). They are also involved in various biological processes, including tumor genesis and fibrosis (Langdahl and others 1997; Suthanthiran and others 2000; Sonia and Jakowlew 2006; Ichinose and others 2007).

In contrast, there are mechanisms involved in the maintenance of peripheral tolerance by regulatory T cells, the function of which depends on the pleiotropic cytokine TGF-β1 (You and others 2006; Kurts 2007; Gao and Wang 2009). Development and progression of renal injuries in patients with DN are also associated with several growth factors and proinflammatory cytokines, including TNF-α, IGF-1, MCP-1, VEGF, and TGF-β1 (Marselli and others 2001).

Although the pathogenic mechanisms underlying T1D and DN are principally different, that is, autoimmunity and inflammation, some common factors, including susceptibility genes and proinflammatory cytokines, are involved in both mechanisms, including infiltrating cell recruitment, up-regulation of other cytokines and chemokines, or apoptosis (Yamada and others 1999; Suthanthiran and others 2000; Marselli and others 2001; You and others 2006). DN is characterized by hypertrophy, increased matrix accumulation and fibrosis, podocyte damage, and thickening of the glomerular basement membrane, leading to renal failure. The key player in the development of pathogenesis in DN is TGF-β1, as reported in many in vitro and in vivo studies (Sharma and Ziadeh 1995; Moitani and others 1998; Zhang and others 2006). In two models of spontaneous T1D, the biobreeding (BB) rat and the non-obese diabetic (NOD) mouse, the development of renal hypertrophy was closely correlated with the increased renal expression of TGF-β1 (Sharma and Ziadeh 1995).

TGF-β1 regulates production of almost every known molecule of the extracellular matrix (Ziyadeh and others 1994; Suthanthiran and others 2000; Wahab and others 2005). Extracellular matrix is involved in the pathogenesis of many diseases, either in the initial triggering or in its aggravation. This is an indication of the crucial role of TGF-β1 in such disorders (Ziyadeh and others 1994; Wahab and others 2005). The central feature of DN is an alteration in the composition of the extracellular matrix, including thickening of the glomerular basement membrane and expansion of the mesangial matrix (Ziyadeh and others 1994; Wahab and others 2005). It is well documented that TGF-β1 plays a potential role in DN (Ziyadeh and others 1994; Sharma and Ziadeh 1995; Linder and others 2003; Ng and others 2003; Patel and others 2005; Wahab and others 2005).

Glucose intolerance is the hallmark of diabetes mellitus. Studies have shown that high glucose induces increase in TGF-β1 (Langdahl and others 1997; Border and Noble 1998). It has been reported that hyperglycemia, increased blood pressure, and genetic predisposition are the main risk factors for the development of DN (Suthanthiran and others 2000). Furthermore, recent studies suggest that inflammatory processes and immune system cells might be involved in development and progression of DN (Suthanthiran and others 2000; Patel and others 2005; You and others 2006). There is a growing body of evidence implicating inflammatory cells at every stage of DN, which produce various proinflammatory cytokines, metalloproteinases, and growth factors that are also associated with the development of T1D (Suthanthiran and others 2000; You and others 2006; Kurts 2007; Gao and Wang 2009).

An increase in TGF-β1 concentration has been proposed to be a factor for the excessive production of extracellular matrix (Ziyadeh and others 1994; Langdahl and others 1997; Yamada and others 1999) proteins seen in diabetes (Suzuki and others 2006). TGF-β1 stimulates glucose uptake by enhancing the expression of GLUT1 in mesangial cells that leads to intracellular metabolic abnormalities in diabetes (Heilig and others 1997).

Further, the progression of T1D is linked to expression of TGF (Zhang and others 2006; Kurts 2007; Gao and Wang 2009). As it has been well documented that TGF-β signaling is critical for CD4+CD25+ T-cell suppression of islet reactive CD8+ T cell in T1D (Bruijin and others 1994; Green and others 2003; You and others 2006). Activated CD4+ and CD8+ T cells act in unison to activate β-cell death via apoptosis. Apoptosis is introduced by activation of the caspase pathway which, in turn, is activated by a number of alternative mechanisms such as Fas interaction with Fas ligand, action of nitric oxide and oxygen-derived free radicals, and membrane disruption by perforin and granzyme B produced by cytotoxic T cells (Green and others 2003).

T-cell cytokines, including IL-1, IFN-γ, and TNF-α, exacerbate β-cell death by up-regulation of Fas and Fas ligand and stimulation of nitric oxide and free radical production. Various cytokines are involved in the enhancement β-cell damage in T1D (Rabinovitch 2003). β-Cell destruction is enhanced by the Th1 and Th17 subsets of CD4+ T cells and cytokines, such as INF-γ, TNF-α, and IL-6, IL-12, IL-17, and IL-18 (Jahromi and others 2000a, 2000b; Rabinovitch 2003; You and others 2006). In patients with T1D, infiltration of mononuclear cells consisting of CD4+ and CD8+ T cells, B cells, and macrophages is observed in islets of pancreas biopsy specimens (You and others 2006; Kurts 2007). In contrast, there are mechanisms involved in the maintenance of peripheral tolerance by a specialized subset of regulatory T cells (Tregs). CD4+ Tregs that constitutively co-express the IL-2R chain (CD4+CD25+) have been shown to play a critical role in controlling undesired immune responses to self-antigens (Green and others 2003; You and others 2006; Kurts 2007). FOXP3 has been shown to be expressed in murine and human CD4+CD25+ Tregs and appears to be a master gene controlling CD4+CD25+ Treg development (Concannon and others 2005; You and others 2006; Kurts 2007). CD4+CD25+ Tregs with a reduced in vitro suppressive function were found in some studies performed on patients with T1D (You and others 2006; Kurts 2007). Treg development and function depend on the pleiotropic cytokine TGF-β1, which is also linked to Th17 cell development (Kurts 2007). These data indicate that there are important candidate regulatory T-cell subsets that show major differences in their functional activities, both in vitro and in vivo. Each population appears to predominantly control a different immune disorder (You and others 2006).

The gene for TGF-β1 is on chromosome 19q13. TGF-β1 gene composed 390 amino acids (Derynck and others 1987). Variations in the TGF-β1 gene sequence might be associated with different effects of TGF-β1 cellular functions (Yamada and others 1998). Several polymorphisms have been reported in the TGF-β1 gene (Ng and others 2003; Patel and others 2005).

Ng and others (2003) have investigated genetic variants in TGF-β1 gene, in codon 10, 25, 263, and two non-coding single-nucleotide polymorphisms (−800 and −509), as well as an insertion/deletion of a cytosine residue in intron 4 (Patel and others 2005). On the other hand, Patel and others (2005) have investigated association of three well-known polymorphisms in the TGF-β1 gene, in codons 10, 25, and 263 with diabetic nephropathy (The Diabetes Control and Complications Trial Research Group 1997). Both groups have worked on Caucasian subjects; however, Patel and others have found a significant association between DN with the TGF-β1 T (29) C in codon 10 (The Diabetes Control and Complications Trial Research Group 1997) while Ng and others have found no association between any of the TGF-β1 gene polymorphisms with DN (Kurts 2007).

Interestingly, production of TGF-β1 varies between individuals and partly depends on polymorphism in the TGF-β1 gene. The T (29) C polymorphism encoding codon 10 change the amino acid from leucine to proline. The substitution of leucine to proline leads to higher level of TGF-β1 (Yamada and others 1998). Due to this phenomenon, association of the T (29) C has been studied in different diseases (Awad and others 1998; Yamada and others 1998; Sonia and Jakowlew 2006).

In order to confirm the possible association of the T (29) C polymorphism of the TGF-β1 gene with T1D as well as diabetic complications, we have genotyped our patients and control groups for the latter gene polymorphism. Association of the TGF-β1 T (29) C gene polymorphism with age at onset and gender of patients with T1D as well as diabetic complications was considered in this small case–control study.

Materials and Methods

Study subjects

The study comprised 388 UK Caucasoid patients with T1D as defined by the National Diabetes Data Group (Derynck and others 1987; Marselli and others 2001); 163 of our patients had different diabetic microvascular complications and 60 patients of which encountered as diabetic control for complication study (Table 1).

Table 1.

Genotype Frequency of TGF-β1 T (29) C with Respect to the Long-Term Complications of Diabetes

Long-term complications of diabetes	TGF-β1 T (29) C genotype
	TT	TC	CC
	n = 68	n = 105	n = 50
DC	20	23	17
DN	14	41	9
DNu	18	19	13
DR	16	22	11

DC, patients who have had diabetes for at least 20 years but remain free of retinopathy and proteinuria.

DN, patients with nephropathy defined as patients who had diabetes for >10 years with persistent proteinuria over 12 months in the absence of hematuria or infection.

DNu, patients with overt neuropathy defined as loss of ankle jerks, sensations of pain, foot ulcer and/or autonomic neuropathy.

DR, patients with retinopathy defined as more than five blots or blots per eye: hard or soft exudates, new vessels or fluorescein angiographic evidence of maculopathy, or previous laser treatment for preproliferative or proliferative retinopathy.

There was a significant increase in the frequency of the TC of the TGF-β1 T (29) C in the patients with nephropathy compared to the diabetic control patients (χ² = 9.56 P = 0.007; RR = 0.598; 95% CI = 0.413–0.866). Although the ratio of CC genotype in diabetic nephropathy patients was different than diabetic controls but was not statistically significant.

Microvascular complications include diabetic neuropathy (nerve damage), diabetic nephropathy (kidney disease), and diabetic retinopathy (eg, glaucoma, cataract, and corneal disease). Patients with overt neuropathy defined as loss of ankle jerks, sensations of pain, foot ulcer, and/or autonomic neuropathy. Patients with nephropathy defined as patients who had diabetes for >10 years with persistent proteinuria over 12 months in the absence of hematuria or infection. Patients with retinopathy defined as more than five blots or blots per eye: hard or soft exudates, new vessels or flourescein angiographic evidence of maculopathy, or previous laser treatment for preproliferative or proliferative retinopathy. Patients who have had diabetes for at least 20 years but remain free of retinopathy, proteinurias are considered as diabetic control for complication study.

Local ethical committee approval has been obtained. The clinical characteristics of the patients are presented in Table 2. High-molecular-weight DNA was prepared from 5–10 mL of EDTA–peripheral blood by using a Nucleon kit, Scotlab, Paisely. Finally, 229 cord blood DNA from sequential newborn Caucasian babies following normal obstetric delivery at Drriford Hospital were used for healthy control subjects. None of our normal controls had any known familial history of autoimmune disorders.

Table 2.

Clinical Characteristic of Patients and Controls

Study subjects	Sex no.	Age (X ± SD)	Age at onset (X ± SD)	Diabetic complication subjects
				DR	DN	Dnu	DC
				n = 49	n = 64	n = 50	n = 60
Patients
M	176	30.1 ± 18.2	14.3 ± 11.2	22	31	22	31
F	212	30.4 ± 18.2	14.4 ± 11.3	17	33	28	29
Controls
M	111	—	—	—	—	—	—
F	118	—	—	—	—	—	—

Abbreviations: DR, diabetic retinopathy; DN, diabetic nephropathy; DNu, diabetic neuropathy; DC, diabetes control: patients with type 1 diabetes who have not shown any complication after 20 years.

In order to amplify T (29) C polymorphism of the TGF-β1 at codon 10 ARMS-PCR methodology was used (Borch-Johnsen and others 1992). In the ARMS-PCR: three amplimers were used; a sense amplimer and tow allele-specific antisense amplimers with T or C alleles at their extremist 3′ ends, underlined. ARMS-PCR amplimers: 5′-TCG GTG GGA TAC TGA GAC AC-3′ (p1); 5′-GCA GCG GTA GCA GCA GCG-3′ (p2); 5′-AGC AGC GGT AGC AGC A-3′ (p3).

Each of p2 or p3 antisense amplimer was used in separate reaction with p1 in a 20 µL reaction. Each PCR consisted of 3.0 µL of genomic DNA (50–150 ng), 1.5 µL of 10 mM MgCl₂, 1.5 µL of Super buffer, and 0.5 µL of DNA polymerase, Taq (HT Biotechnology, UK), 0.5 µL of NTPs.

For the T-allele reaction 15 pmol of p3 and 9 pmol of p1 were used, and for the C allele reaction 9 pmol of p2 and 9 pmol of p1 were used. Each reaction mixture was added up to 20.0 µL by sterilized water.

The thermocycling procedure consisted of an initial denaturation at 95°C for 1 min and 15 s 95°C, 50 s 65°C, and 50 s 72°C for 10 cycles followed by 20 cycles of 20 s 95°C, 40 s for 58°C, and 50 s 72°C. The PCR products were analyzed by 2% agarose gel electrophoresis and visualized by ethidium bromide staining.

Practical part of this work was conducted in Molecular Medicine Research Group, Peninsula Medical School, Plymouth, UK. However, statistical analyses were performed in Department of pathology, Salmaniya Medical Complex, Kingdom of Bahrain.

Genotype and allele frequencies were estimated by the gene counting method, departures from Hardy–Weinberg equilibrium were tested using a χ²-test. We used the Fisher’s exact test to compare the proportion of association of different genotypes among patients and normal healthy subjects and to compare association of different genotypes among gender and age at onset subjects.

Results

The T (29) C in the polymorphic region in exon 1 of the TGF-β1 gene that results in a transitions of Leu to Pro at amino acid 10 was accurately detected using the ARMS-PCR methodology. The frequencies of TT, TC, and CC in our patients with T1D were 26.0, 53.9, and 20.1, respectively (Table 3).

Table 3.

Genotype and Allelic Frequency and Distribution of the T (29) C Polymorphism at Codon 10 of TGF-β Gene

Genotype	Controls	Patients	χ²	P value	RR	95% CI
TT	74	102	2.28	ns
TC	80	208	19.43	0.00001	0.613	0.492–0.765
CC	75	78	11.68	0.0005	1.477	1.201–1.816
T	137	249	ns
C	109	209	ns

TC genotype shows a significant association with type 1 diabetes. The frequency of CC is significantly more in normal controls compared with the patients.

Allelic distribution of the T (29) C polymorphism in codon 10 of TGF-β does not show a significant association with type 1 diabetes.

Abbreviations: CI, confidence interval; RR, relative risk; TGF, transforming growth factor.

The genotype and allelic distribution of the T (29) C in the TGF-β1 gene were calculated. The frequency of TC showed a significant association with T1D, χ² = 19.43, P = 0.00001, relative risk (RR) = 0.612, 95% confidence interval (CI) = 0.492–0.765. However, allelic distribution frequencies showed no considerable association (Table 3). On the other hand, the TGF-β1 C C genotype decreased significantly in patients compared to normal controls, χ² = 11.68, P value = 0.0005, RR = 1.477, 95% CI = 1.201–1.816 (Table 3).

There was a significant increase in the frequency of the TC in the patients with DN compared to the diabetic control patients, χ² = 9.56, P = 0.007, RR = 0.598, 95% CI = 0.413–0.866 (Table 1). No other significant association was found between the genotype of the TGF-β1 T (29) C and the long-term complications of diabetes (Table 1).

There has been no significant difference between the genotype frequency of T (29) C polymorphism in the TGF-β1 gene with regard to the gender and/or age at onset of patients with T1D.

Discussion

We have screened our patients with T1D for the T (29) C polymorphism in codon 10 of the TGF-β1 gene using ARMS-PCR. The ARMS-PCR is a fast and one of the most accurate techniques to detect possible variations in gene sequences. There was a strong and significant association between the TC genotype with T1D, P = 0.00001. No significant association between the TT and CC genotype with T1D was detected. However, the CC genotype was less common in patients than in control subjects, P = 0.005 (see Table 3). Further, in order to examine the strength of genotype susceptibility of the T (29) C polymorphism in the TGF-β1 gene in diabetic long-term complications, this polymorphism has been considered in patients with DN, diabetic retinopathy, and diabetic neuropathy. Meanwhile, a group of diabetic control, patients with T1D who have not shown any type of complications after 20 years of the disease, was included as controls for diabetic complication study. A significant increase was found in the frequency of the TC in the patients with DN compared with the diabetic controls. No other significant association was found between the T (29) C polymorphism in the TGF-β1 gene with diabetes long-term complications. According to Yamada and others (1998), the TC genotype has been reported as the medium producer of TGF-β1 protein (Yamada and others 1998). T1D is a T-cell-mediated disease (Berman and others 1996; Jahromi and others 2000a). As a result of the deviation of the Th1/Th2 balance to Th1-dominant cytokine milieu, the immune system recruits Th2–Th17 or Th3 cells to produce immunosuppressor cytokines such as TGFβ1 (You and others 2006; Kurts 2007). Association of the TC (moderate producing) and not the CC or TT (high- or low-producing) genotypes of TGF-β1 could be due to: (1) the TC being more diabetogenic than other two genotypes; (2) TGF-β1 production being dependent on the C29 allele, hence, less TGF-β1 production than C29C; (3) expression study was not performed by us; and (4) malfunction of the gene or protein due to the PPI that may lead to different T-cell mechanisms (You and others 2006). On the other hand, the CC genotype was significantly increased in control group compared to patients group. The CC genotype is associated with high TGF-β1 protein level that may explain the immune regulatory effects of TGF-β1 in normal healthy individual as the safeguard for any possible elevation of the Th1/Th2 balance.

Further, the TC genotype showed significant increase in patients with DN among other diabetic complication groups compared to diabetic control, P = 0.007 (Table 3).

An increasing evidence has been collected through the years regarding the molecular mechanisms involved in developing T1D or DN (Quinn and others 1996; You and others 2006). Although the pathogenic mechanisms underlying T1D and DN are principally different, that is, autoimmunity (metabolic syndrome) and inflammation (nephritic syndrome), some common factors, including susceptibility genes and proinflammatory cytokines, are involved in both mechanisms including infiltrating cell recruitment, up-regulation of other cytokines and chemokines, or apoptosis. These include MCP-1, TGF- β1, SUMO 1, TNF-α, IL-6, IFN-γ, IL-18, and MBL, and so on (Jahromi and others 2000b; Lalioti and others 2002; Green and others 2003; You and others 2006).

Association of the TGF-β1 TC genotype with both syndromes may genetically reveal an interesting phenomenon of dual effects of TGF-β1 in the early onset of T1D and progression of fibrosis of kidney that leads to kidney failure in DN. Dual actions of the TGF-β1 have been reported in several occasions (You and others 2006; Gao and Wang 2009). However, according to the literature our study is the first report about the dual action of the TGF-β1 gene in T1D as well as DN. Association of the TGF-β1 gene polymorphisms with T1D and DN in Caucasian populations have been studied by Ng and others and Patel and others (Ng and others 2003; Patel and others 2005). Although Ng group has reported negative association of the TGF-β1 gene polymorphisms with DN, Patel group has reported a significant association with the TGF-β1 T (29) C gene polymorphism in codon 10. Our finding also is in complete agreement with Patel group. However, we have correlated our findings with the functional ability of different TGF-β1 T (29) C gene polymorphism genotypes.

In fact, association and lack of association have been reported in different Caucasian populations previously (Langdahl and others 1997; Awad and others 1998; Yamada and others 1998, 1999; Jahromi and others 2000b; Suthanthiran and others 2000; You and others 2006; Chinoy and others 2007; Ichinose and others 2007; Little and others 2008).

This is a small case–control study of association of polymorphism in codon 10 of the TGF-β1 T (29) C gene with T1Dand DN in UK Caucasian study. Recently due to the advancement of biotechnology, association studies are conducted on hundreds if not thousands of samples (Aly and others 2008; Barrett and others 2009); therefore the impact of these results should be considered in the light of the above comments. Extensive research for clarifying the pathogenesis of DN in diabetes may lead to the unexpected new findings for the understanding the etiology of T1D.

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