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Resequencing of genes for transforming growth factor β1 (TGFB1) type 1 and 2 receptors (TGFBR1, TGFBR2), and association analysis of variants with diabetic nephropathy

  • Amy Jayne McKnight1, 3Email author,
  • David A Savage1,
  • Chris C Patterson2,
  • Denise Sadlier4 and
  • A Peter Maxwell1
BMC Medical Genetics20078:5

DOI: 10.1186/1471-2350-8-5

Received: 03 August 2006

Accepted: 23 February 2007

Published: 23 February 2007

Abstract

Background

Diabetic nephropathy is the leading cause of end stage renal failure in the western world. There is substantial epidemiological evidence supporting a genetic predisposition to diabetic nephropathy, however the exact molecular mechanisms remain unknown. Transforming growth factor (TGFβ1) is a crucial mediator in the pathogenesis of diabetic nephropathy.

Methods

We investigated the role of five known single nucleotide polymorphisms (SNPs) in the TGFB1 gene for their association with diabetic nephropathy in an Irish, type 1 diabetic case (n = 272) control (n = 367) collection. The activity of TGFβ1 is facilitated by the action of type 1 and type 2 receptors, with both receptor genes (TGFBR1 and TGFBR2) shown to be upregulated in diabetic kidney disease. We therefore screened TGFBR1 and TGFBR2 genes for genomic variants using WAVE™ (dHPLC) technology and confirmed variants by direct capillary sequencing. Allele frequencies were determined in forty-eight healthy individuals. Data for all SNPs was assessed for Hardy Weinberg equilibrium, with genotypes and allele frequencies compared using the χ2 test for contingency tables. Patterns of linkage disequilibrium were established and common haplotypes estimated.

Results

Fifteen variants were identified in these genes, seven of which are novel, and putatively functional SNPs were subsequently genotyped using TaqMan™, Invader™ or Pyrosequencing® technology. No significant differences (p > 0.1) were found in genotype or allele distributions between cases and controls for any of the SNPs assessed.

Conclusion

Our results suggest common variants in TGFB1, TGFBR1 and TGFBR2 genes do not strongly influence genetic susceptibility to diabetic nephropathy in an Irish Caucasian population.

Background

Diabetic nephropathy is a major clinical complication of diabetes mellitus. Epidemiological evidence supporting a genetic contribution to this disease includes ethnicity differences [1], familial clustering [2, 3] and the fact that only a subset of individuals with type 1 diabetes develops diabetic nephropathy regardless of metabolic control [4]. In addition, simulation studies have shown that environmental effects are insufficient to account for the familial aggregation of this disease [3, 5].

Transforming growth factor beta (TGFβ1) is a multifunctional cytokine implicated in the pathogenesis of many forms of progressive renal disease, including diabetic nephropathy, by promoting renal hypertrophy and the accumulation of extracellular matrix [6]. Protein and mRNA levels of TGFβ1 are significantly increased in the renal glomeruli and tubulointerstitium of animal models of diabetes and in humans with diabetes [7]. TGFβ1 is transcriptionally activated by high extracellular glucose in murine glomerular mesangial cells [8]. Transgenic mice over-expressing TGFβ1 develop progressive renal failure, suggesting that chronically elevated levels of circulating TGFβ1 are integral to the pathogenesis of kidney disease [9, 10]. Direct blockade of TGFβ protein by chronic administration of anti-TGFβ1 antibodies has been shown to decrease renal insufficiency [11]. In addition, antisense TGFβ1 oligonucleotides reduce the cellular hypertrophy and stimulation of matrix synthesis normally seen in renal cells exposed to high extracellular glucose [12].

The activity of TGFβ1 in regulating cell proliferation, differentiation and extracellular matrix production are mediated by a heterodimeric complex of type 1 and type 2 receptors. Upregulation of TGFβ1 receptors have been reported in animal models of glomerulosclerosis [13, 14]. It has been proposed that upregulation of TGFβR2 induced by high extracellular glucose may contribute to distal tubular hypertrophy in diabetic nephropathy [15]. Isono and colleagues demonstrated that increased expression of TGFβR2 in the diabetic kidney is primarily due to stimulation of gene transcription rather than increased mRNA stability [16].

TGFβ1 is encoded by the TGFB1 gene located at chromosome 19q13.1 [17]. We have investigated the role of five known single nucleotide polymorphisms, which may influence TGFB1 gene expression (TGFB1: -800G>A, -509C>T, +72InsC, +869T>C, +915G>C) for their association with diabetic nephropathy. TGFβ receptors type 1 and type 2 are encoded by TGFBR1 and TGFBR2 genes respectively. At present there are over six hundred variants recorded in dbSNP for these genes, with little information available on the role of these variants in relation to renal complications of diabetes. We have screened the genomic draft sequence for the TGFBR1 and TGFBR2 genes in an Irish population to identify genomic variants. Allele frequencies were subsequently determined in a healthy control population and selected SNPs genotyped in a case-control collection. In summary, we investigated if putatively functional variants in three genes, TGFB1, TGFBR1 and TGFBR2, contribute to genetic susceptibility to diabetic nephropathy in type 1 diabetes.

Methods

Subjects

Ethical approval was obtained from the appropriate Research Ethics Committees in each country and written, informed consent obtained from individuals prior to conducting this study. The case and control groups used for this study (Table 1) have been described previously [18]. All patients were at least third generation Irish Caucasians diagnosed with type 1 diabetes mellitus before 31 years of age, and required insulin from diagnosis. Patients with nephropathy (cases, n = 272) had diabetes for at least 10 years before the onset of proteinuria (>0.5 g/24 h). Patients without nephropathy (controls, n = 367) had diabetes for at least 15 years, were not in receipt of antihypertensive medication, and had no evidence of non-diabetic renal disease. Patients with microalbuminuria were excluded from both groups.
Table 1

Clinical characteristics of cases (n = 272) and controls (n = 367) (Data are n, mean ± SD)

Criteria

Cases

Controls

N

272

367

Gender

  

Male

61.4 %

40.3 %

Female

38.6 %

59.7 %

Age at Diagnosis (years)

17.1 ± 8.2

16.8 ± 8.1

*Duration of Diabetes (years)

26.9 ± 8.3

27.7 ± 9.0

HbA1 C (%)

8.5 ± 1.7

8.4 ± 1.6

BMI (kg/m2)

26.0 ± 3.8

26.2 ± 3.5

Systolic Blood Pressure (mm Hg)

150.1 ± 22.6

126.9 ± 16.6

Diastolic Blood Pressure (mm Hg)

86.5 ± 11.4

76.1 ± 7.3

* Duration of diabetes was calculated from the date of diagnosis of diabetes to date of recruitment

* BMI = body mass index

In silicoanalysis

For TGFBR1, the nucleotide sequence of draft clone RP11-96L7 for human chromosome 9 was downloaded from the National Centre for Biotechnology Information [19]. Similarly, the sequence for TGFBR2 was obtained for draft clone RP11-1024P17 on human chromosome 3. Reference mRNA (NM_004612; NM_003242) and protein (NP_004603; NP_003233) sequences were also downloaded from NCBI for TGFBR1 and TGFBR2 respectively. These were used to determine intron-exon boundaries for genomic DNA using Vector NTI Advance (suite 2, version 8, Informax Inc (Europe), Oxford, UK). The nomenclature for all identified variants follows the Human Genome Variation Society recommendations for coding sequences, updated 21st May 2005 [20]. In addition, we have provided rs numbers for all previously identified SNPs and ss numbers for novel SNPs to facilitate ease of comparison between research groups.

Amplification and mutation screening

6464 bases of TGFBR1 and 5204 bases of TGFBR2 genomic sequences were divided into fragments with an average size of approximately 500 base pairs, for PCR and screening purposes in 15 case and 15 control individuals. As the TGFBR1 and TGFBR2 gene sequences cover approximately 45 kb and 84 kb respectively from start to stop codon, only the coding regions of these genes (including all exons, exon-intron boundaries and untranslated regions) were screened to prioritise the identification of potentially functional gene variants. Each PCR product was then evaluated using WaveMaker v3.4 software (Transgenomic Ltd, Crewe, UK) and analysed on the WAVE™ (dHPLC) DNA Fragment Analysis System (Transgenomic Ltd) following the manufacturer's recommendations. Differentially separating fragments (representing DNA variants) were bidirectionally sequenced to identify variants using an ABI PRISM® 3100 Genetic Analyser (Applied Biosystems, Warrington, UK). Forty-eight healthy controls (n = 96 chromosomes) from the Young Hearts collection [21] (a healthy Irish Caucasian population) were genotyped by direct capillary sequencing (Applied Biosystems) to establish allele frequencies for all gene variants.

Genotyping

Five SNPs were selected for genotyping in the TGFB1 gene as they have been previously suggested to influence the expression of TGFβ1, in addition to demonstrating a minor allele frequency greater than 5%. TaqMan assays were successfully designed for TGFB1: -800G>A (rs1800468), TGFB1: -509C>T (rs1800469), TGFB1: +869T>C (rs1982073) and TGFB1: +915G>C (rs1800471) SNPs, but proved problematic for TGFB1: +72InsC (rs1800999) due to the presence of a long C homopolymer. TGFB1: +72InsC was successfully genotyped using a biplex Invader™ assay (Third WAVE Technologies Inc, Madison, MI, USA). Genotyping was performed for receptor variants using Pyrosequencing® technology according to the manufacturer's instructions (Biotage, Uppsala, Sweden). Details of the primer sequences used for resequencing purposes, together with the WAVE conditions and the oligos used for the genotyping assays are listed (Tables 2, 3, 4, 5) with further details readily available from the authors on request. 272 case and 367 control samples were available for genotyping TGFB1 SNPs, however fewer samples were available (241 cases and 322 controls) for genotyping TGFBR2 gene variants. Genotype frequencies were assessed for Hardy-Weinberg equilibrium using a χ2 goodness-of-fit test. The χ2 test for contingency tables was used to compare genotype and allele frequencies between case and control subjects with the level of significance set to p < 0.05. Haploview [22] was used to visualise linkage disequilibrium (LD) and haplotype blocks within each gene.
Table 2

Primer sequences used for screening TGFBR1 and TGFBR2 genes

Primer Set

Primer 1

Primer 2

TGFBR1 i

tcctccttaaaaggttctgc

agaaagtcctcagatcccag

TGFBR1 ii

ggaggctatttgggggtgt

gcgagcgccggtttctg

TGFBR1 iii

actcacacagacacaccca

aagagcaggagcgagccag

TGFBR1 iv

ctaagagcaacaaacagtgc

gtcacttcttgcctctaaacg

TGFBR1 v

tgcaggaattgtgtaggattg

tggagctgacttattgattcg

TGFBR1 vi

ctccccagtgagataaattc

aatcttgaagaagttcctag

TGFBR1 vii

gcttactctgaggaactaaag

agatgcggttttgtcatgttg

TGFBR1 viii

aagtattgtaggtcatgtgg

gatattttctggaagggcaac

TGFBR1 ix

gtctgaaaggaggttcatc

caggaagagaatacactagg

TGFBR1 x

gtgatcttttaatgccttgg

aacattggtttgactgcta

TGFBR1 xi

caccagtaccctattgatgg

aaggagagttcaggcaaagc

TGFBR1 xii

gcaactcagtcaacaggaag

gaatcaaggaaactctagtgg

TGFBR1 xiii

agaaagtgatttactcct g

attcaaacatgaccatgc

TGFBR1 xiv

ctttctcctaccaaaatgtgc

ctgaattaaaagctgccttcc

TGFBR2 i

cctcctggctggcgagcg

ggaccaaacgtgccccgc

TGFBR2 ii

aagcaaatggctactcaacc

acacatacatgcagagaacacc

TGFBR2 iii

tgcgaatgctggagaacagg

ggaggacaccacctaacgtatg

TGFBR2 iv

agctgaagtttgaaggaagagc

gcacacggttgttgtagttggt

TGFBR2 v

catcatcttctactgctaccgc

ggttcccgttggatgtcctcat

TGFBR2 vi

ggagttggggaaacaatactgg

gggtcaagtcgtgtaaaaaagg

TGFBR2 vii

ctatctgtacctttctgtgc

ccaatacgatttgtcggatc

TGFBR2 viii

gttacttagtgcttcatgctcc

ccttccagggtaacacaagata

TGFBR2 ix

gtgttgggagtgttagtgtacc

ccgtaggtctaccacacactct

TGFBR2 x

accaactcatggtgccctttgg

cggtatggaacttttctctg

TGFBR2 xi

gctgtgttagcacttcctcagg

ggtttagaccccccgatcaaat

TGFBR2 xii

tgtttgaggaccagtgttcccg

ccgaggactaacgagttcgtgt

Table 3

WAVE conditions used for screening TGFBR1 and TGFBR2 genes.

Primer Set

Tm°C

Melt Range°C

Run Temperature°C

WAVE Buffer B (%)

TGFBR1 i

59.4

54 – 72

57

69–79

   

59

67–77

   

64

62–64

TGFBR1 ii

63.3

60 – 72

63

68–78

   

69

62–72

TGFBR1 iii

69.2

58 – 75

69

68–78

   

72

65–75

TGFBR1 iv

55.9

54 – 65

55

68–78

   

59

64–74

TGFBR1 v

57.2

54 – 65

55

62–72

   

59

58–68

   

61

56–58

TGFBR1 vi

56.1

54 – 65

56

68–78

   

59

65–75

TGFBR1 vii

56.5

54 – 68

55

69–79

   

58

66–76

TGFBR1 viii

57.0

54 – 65

57

67–77

TGFBR1 ix

57.4

55 – 67

56

67–77

   

58

64–75

   

62

61–71

TGFBR1 x

54.8

51 – 66

54

65–75

   

57

62–72

TGFBR1 xi

54.6

54 – 67

54

65–75

   

58

60–70

TGFBR1 xii

56.9

55 – 65

56

64–77

   

58

62–72

TGFBR1 xiii

55.8

52 – 62

56

67–77

TGFBR1 xiv

55.2

54 – 63

55

67–77

   

59

63–73

TGFBR2 i

66.1

59–74

60

63–73

   

65

58–68

   

67

56–66

   

70

53–63

TGFBR2 ii

66.3

61 – 72

64

58–68

   

66

56–66

   

69

52–62

TGFBR2 iii

58.5

57 – 61

59

61–71

   

61

59–69

TGFBR2 iv

59.8

55 – 65

56

67–77

   

61

60–70

   

63

58–68

TGFBR2 v

60.5

57–64

62

58–68

TGFBR2 vi

63.5

62–65

64

55–65

TGFBR2 vii

59.7

53–71

59

57–67

   

61

52–62

TGFBR2 viii

59.7

53 – 71

59

66–76

   

61

64–74

TGFBR2 ix

61.0

60–61

61

57–67

TGFBR2 x

57.0

51–66

52

63–73

   

58

57–67

   

62

53–63

   

64

50–60

TGFBR2 xi

54.4

53 – 66

54

67–77

   

56

65–75

   

60

61–71

TGFBR2 xii

57.0

56–60

59

63–73

Table 4

TaqMan primers, probes, quencher and annealing temperature for relevant assays.

Primer set

Primer 1

Primer 2

FAM™ Labelled Probe

Vic™ Labelled Probe

Fluorescent Quencher

Anneal (1 minute)

TGFB1 -800G>A

gctatcgcctgcacacagc

aggacagaagcggtcccat

tgcctccaacgtcaccaccatc

tctgcctccaacatcaccaccatc

TAMRA

62°C

TGFB1 -509C>T

ttagccacatgggaggtgct

ccaggcggagaaggcttaa

acccttccatccctcaggtgtcct

ccctcccatccttcaggtgtcctg

TAMRA

62°C

TGFB1 +869T>C

caccacaccagccctgttc

ccaggcgtcagcaccagta

agcagcggcagca

cagcagcagcagc

None

60°C

TGFB1 +915G>C

Developed by Applied Biosystems (USA) as a Research and Development Kit

None

56°C

TGFBR1+72InsC was genotyped by a commercial Invader kit designed and manufactured by Third WAVE technologies (Madison, MI, USA)

Table 5

Pyrosequencing primers, dispensation order and sequence to analyse for relevant assays

Primer Set

Forward Primer

Reverse Primer

Sequence Primer

Dispensation order

Sequence to Analyse

TGFBR2 c.*747C>G

tcctgtgtgcccttatttctc

tgaaggtaaaaagtggggttc

agtttctaaactaggttgag

tcgagagtctac

c/ggagagtttctaaac

TGFBR2 c.1149G>A

gatcacactccatgtggg

ccagacgcagggaaagc

agagctccaatatcctc

tgatgagacgac tac

g/atgaagaacgacctaacc

Results

We have submitted our annotated sequencing data for TGFBR1 and TGFBR2 genes as GenBank accession numbers DQ383416 – DQ383424 and DQ377553 – DQ377559 respectively. A total of fifteen variants were identified in these genes (TGFBR1, n = 5; TGFBR2, n = 10) of which eight were previously recorded in dbSNP; we have obtained unique NCBI identifiers for all novel SNPs (n = 7; Table 6).
Table 6

Minor allele frequencies of identified variants in TGFBR1 and TGFBR2 genes, based on genotyping of 48 healthy control individuals. Accepted GenBank accession numbers for the reference sequences describing TGFBR1 and TGFBR2 gene variants are DQ383416 – DQ383424 and DQ377553 – DQ37759 respectively.

Variant

Unique NCBI Identifier

Minor Allele Frequency (%)

a TGFBR1: c.694A>C

ss50394789

4.3

a TGFBR1: c.*899T>C

ss50394790

2.2

a TGFBR1: c.*921T>G

ss50394793

4.3

a TGFBR1: c.*978G>A

ss50394791

1.1

a TGFBR1: c.*1004A>T

ss50394792

2.2

TGFBR2: c.263+7A>G

rs1155705

10.8

a TGFBR2: c.263+17A>C

ss50394787

1.1

TGFBR2: c.445-111A>G

rs17026161

2.2

TGFBR2: c.445-4T>A

rs11466512

21.7

a TGFBR2: c.1149G>A

ss50394788

1.1

TGFBR2: c.1157C>T

rs2228048

2.2

TGFBR2: c.1515-91C>A

rs2276767

4.3

TGFBR2: c.*327-329delAT

rs4016180

21.7

TGFBR2: c.*747C>G

rs11466531

7.6

TGFBR2: c.*835C>A

rs17026332

2.2

a Novel SNPs accepted by dbSNP

The distribution of genotypes was found to be in Hardy-Weinberg equilibrium for all SNPs in both case and control groups. No significant differences were observed in genotype and allele frequencies between case and control groups for any of the SNPs assessed (Table 7). Logistic regression analysis for the clinical characteristics described in Table 1 did not reveal a significant association with any variant and diabetic nephropathy. Adjusted p values for these potential covariates are shown in Table 8.
Table 7

Genotype and allele frequencies of selected SNPs in case and control groups. The five TGFB1 SNPs were selected on the basis of previous publications [23-27]. The remaining two TGFBR2 SNPs were selected from potentially functional SNPs identified through screening the gene as summarised in Table 1. Data are n (%)

SNP

Genotype

Case

Control

pvalue

Allele

Case

Control

pvalue

TGFB1 -800G>A

GG

188 (69.1)

268 (73.0)

0.56

G

454 (83.5)

628 (85.6)

0.30

 

GA

78 (28.7)

92 (25.1)

     
 

AA

6 (2.2)

7 (1.9)

 

A

90 (16.5)

106 (14.4)

 

TGFB1 -509C>T

CC

179 (65.8)

245 (66.8)

0.62

C

442 (81.3)

595 (81.1)

0.93

 

CT

84 (30.9)

105 (28.6)

     
 

TT

9 (3.3)

17 (4.6)

 

T

102 (18.7)

139 (18.9)

 

TGFB1 +72InsC

- C

221 (81.3)

301 (82.0)

0.88

- C

488 (89.7)

663 (90.3)

0.71

 

+/- C

46 (16.9)

61 (16.6)

     
 

+ C

5 (1.8)

5 (1.4)

 

+C

56 (10.3)

71 (9.7)

 

TGFB1 +869T>C

TT

151 (55.5)

204 (55.6)

0.86

T

403 (74.1)

540 (73.6)

0.84

 

TC

101 (37.1)

132 (36.0)

     
 

CC

20 (7.4)

31 (8.4)

 

C

141 (25.9)

194 (26.4)

 

TGFB1 +915G>C

GG

219 (80.5)

298 (81.2)

0.98

G

488 (89.7)

661 (90.1)

0.84

 

GC

50 (18.4)

65 (17.7)

     
 

CC

3 (1.1)

4 (1.1)

 

C

56 (10.3)

73 (9.9)

 

a TGFBR2 c.*747C>G

CC

218 (90.5)

287 (89.1)

0.88

C

457 (94.8)

606 (94.1)

0.61

 

CG

21 (8.7)

32 (9.9)

     
 

GG

2 (0.8)

3 (0.9)

 

G

25 (5.2)

38 (5.9)

 

a TGFBR2 c.1149G>A

GG

232 (96.3)

317 (98.4)

0.10

G

473 (98.1)

639 (99.2)

0.10

 

GA

9 (3.7)

5 (1.6)

     
 

AA

0

0

 

A

9 (1.9)

5 (0.8)

 

a 272 cases and 367 controls were genotyped for TGFB1 SNPs with 241 cases and 322 controls genotyped for TGFBR2 variants.

Table 8

Significance values following logistic regression analyses adjusting the association between diabetic nephropathy status and genotype for the listed potential confounders.

pvalue adjusted for:

TGFB1-800G>A

TGFB1-509C>T

TGFB1+72InsC

TGFB1+869T>C

TGFB1+915G>C

TGFBR2c.*747C>G

TGFBR2c.1149G>A

-

0.56

0.62

0.89

0.86

0.98

0.88

0.11

Gender

0.56

0.45

0.98

0.92

0.94

0.88

0.09

Age at Diagnosis

0.56

0.61

0.88

0.86

0.98

0.88

0.11

Duration of Diabetes

0.62

0.69

0.94

0.94

0.98

0.56

0.26

HbA1c

0.44

0.63

0.96

0.80

0.97

0.86

0.16

BMI

0.79

0.72

0.63

0.79

0.97

0.22

0.72

Mean BP

0.94

0.93

0.68

0.99

0.77

0.31

0.85

All of the above

0.36

0.94

0.93

0.70

0.96

0.49

0.95

The level of observed LD between all genotyped variants within each gene, together with the raw |D'| and R2 scores are shown in the Figures (Figures 1, 2). The most common combinations of alleles observed 5' to 3' were GC-TG (49.4%); AC-TG (12.6%) and GT-CG (10.5%). In addition, we have identified a novel, rare variant at TGFB1: +728T>C (ss50394786).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2350-8-5/MediaObjects/12881_2006_Article_199_Fig1_HTML.jpg
Figure 1

Although |D'| values were not particularly large for TGFB1 markers (D' Plot), they were statistically significant. R2 measure, there was little correlation observed between the genotyped markers (R2 Plot). Further details are displayed in the descriptive shown tables below the LD Plots. D' is the value of D primer between the two loci; LOD is the log of the likelihood odds ration (a measure of confidence in the value of D'); R2 is the correlation coefficient between the two loci and CI low/CI high represent 95% confidence limits for D' where the minor allele frequency is greater than 5%.

https://static-content.springer.com/image/art%3A10.1186%2F1471-2350-8-5/MediaObjects/12881_2006_Article_199_Fig2_HTML.jpg
Figure 2

Strong linkage disequilibrium was not observed between the two genotyped markers for TGFBR2. Further details are displayed in the descriptive tables shown below the LD Plots.

Discussion

There is considerable evidence supporting the role of TGFB1, TGFBR1 and TGFBR2 genes in the development of diabetic nephropathy. The functional importance of the TGFβ1 protein is illustrated by the high degree of conservation observed across mammalian species. The TGFβ1 gene comprises seven exons separated by relatively large introns [23]. Transcriptional regulation is complex with two major start sites identified at positions +1 and +271 [24]; polymorphic positions are typically reported relative to the first major transcription start site for this gene. We have assessed five SNPs, suggested to play a role in TGFβ1 expression levels through their impact on regulatory regions of TGFB1 [2527], for association with diabetic nephropathy. Genotype and allele frequencies were similar to those reported in other European populations, with a decreased frequency observed for the minor alleles of TGFB1: -509C>T and TGFB1: +869T>C compared to the ECTIM results [25, 28, 29]. As illustrated by the LD Plots (Figures 1, 2), we observed low correlation between the genotyped SNPs. The |D'| values suggest that these SNPs have been separated by recombination, however as the magnitude of |D'| is biased for smaller sample sizes |D'|, lower values may be difficult to interpret. To further clarify the patterns of LD between genetic markers, we also examined R2 values as this measure of LD is not as susceptible to small sample sizes. It is important to note that |D'| is less than one only when all haplotypes are observed and that markers with disparate alleles frequencies will also affect these measures of LD. The patterns of LD indicate that all genotyped loci within each gene are not contained within a single haplotype block, thereby suggesting limited value in performing haplotype analysis – i.e. the LD values suggest that these markers are not transmitted on a single haplotype, but are separated by recombination events. Our analysis suggests that all SNPs genotyped in this study are informative and the most common combinations of alleles observed are similar to those previously published [29]. Comparison of our data with Phase II, release 21 of the HapMap resource [30] supports our findings that the TGFB1 gene is located in a genomic region affected by a recombination hotspot. All recorded polymorphic sites in the HapMap CEPH (Utah residents with ancestry from northern and western Europe) population demonstrate poor correlation, suggesting that all should therefore be genotyped as 'tag' SNPs. None of the common variants genotyped for the TGFB1 gene in this study are recorded as polymorphic in the Phase II, release 21 HapMap Caucasian data set and the nearest polymorphic SNP is approximately 2 kb from our SNPs of interest.

We observed no significant differences in genotype or allele frequencies between case and control groups for any of the SNPs assessed. The TGFB1: +869T>C SNP has been associated with diabetic nephropathy in a Chinese population with type 2 diabetes [31], however our results do not support this finding for nephropathy in type 1 diabetes. The results from Wong and colleagues' smaller Chinese study (cases, n = 58; controls, n = 65), may be explained by a difference in genetic factors between type 1 and type 2 diabetes or differences between the Chinese and Irish populations.

Our study employed rigorous phenotypic criteria for inclusion of cases and controls. The annual incidence of diabetic nephropathy increases over the first fifteen to twenty years duration of type 1 diabetes, but after twenty-five years the absence of overt proteinuria makes the subsequent development of nephropathy unlikely [32, 33]. The present report utilised cases and controls that were well matched for prolonged duration of diabetes (cases mean duration = 26.9 ± SD 8.3 years, control mean duration = 27.7 ± SD 9.0years). Our results for TGFB1 are in accord with Ng and colleagues' study which also failed to find an association between the TGFB1: -800G>A, -509C>T, +869T>C or +915G>C polymorphisms and diabetic nephropathy in US Caucasians with type 1 diabetes [34]. This is in contrast to a larger study in UK Caucasians where a significant association (p = 0.027) was identified between TGFB1: +869T>C and diabetic nephropathy [35]. This UK study utilised the Golden Years cohort of type 1 diabetic individuals as a control population [31] with all the recruited subjects (n = 410) having a very long duration of type 1 diabetes (> 50 years). Although these individuals did not have renal failure due to diabetic nephropathy 29% were taking antihypertensive medication and 35.7% had evidence of micro- or macroalbuminuria [36]. These clinical features (antihypertensive medication and micro- or macroalbuminura) form distinct exclusion criteria from our own diabetic control group. Although our sample size has ~90% power to detect a doubling in the minor allele frequency in cases relative to controls (e.g. 10% vs. 5%), there is a need for a collaborative genotyping effort in larger sample collections to definitively determine the role of these SNPs in predisposition to diabetic nephropathy.

TGFβ type I receptors form a heterodimeric complex with TGFβ type II receptors and bind to TGFβ to mediate many TGFβ activities including regulation of cell proliferation, differentiation and extracellular matrix production. It has been recently reported that TGFβ1-mediated epithelial-to-mesenchymal transition requires functional TGFBR2 [37]. Variants have been recorded for both TGFBR1 and TGFBR2 genes, however there is limited genomic information regarding their influence on diabetic nephropathy. TGFBR1 is composed of nine exons and maps to chromosome 9q33-q34 [38]. TGFBR2 is composed of seven exons and maps to 3p22 [39]. There are presently 409 validated SNPs recorded in dbSNP for these two genes (TGFBR1, n = 115; TGFBR2, n = 294; dbSNP, accessed 12/01/06). Due to the large number of reported SNPs and potential ethnic variation in SNP occurrence and frequency [40], we resequenced these genes in our population.

We prioritised screening of the protein coding regions of these genes to aid identification of potentially functional gene variants. We screened for variants directly affecting lariat regions, splice sites, exonic/intronic splice enhancers, signal sequences, protein coding sequence, polyadenylation signals and untranslated regions. It is possible that other variants may affect regulatory mechanisms, (promoter or enhancer elements, microRNA etc.) or that features such as post-translation modifications may affect these candidate genes and their subsequent protein activity. It is also possible that rare variants may play a role in susceptibility to diabetic nephropathy; however this study lacks sufficient sample numbers to definitively assess the role of rare variants in this disease. Five novel variants were identified in TGFBR1, of which none were at sufficient frequency to assess in this case-control collection. We have identified nine SNPs in TGFBR2. Two SNPs are located in exons (TGFBR2: c.1157C>T, TGFBR2: c.1149G>A) and one SNP in the 3' UTR which was found to be putatively functional (TGFBR2: c.*747C>G). Analysis of TGFBR2: c.*747C>G genotyping did not reveal a significant association with diabetic nephropathy. A microsatellite [AT]del was also identified in the 3' UTR of TGFBR2. TGFBR2: c.1157C>T in exon four was found in only one sample in the heterozygous state (MAF: 1.1%), and does not lead to a change in amino acid (aac → aat = N389N). TGFBR2: c.1149G>A was found in only two samples (MAF: 2.2%), but leads to a non-synonymous change in amino acid (gtg → atg = V387M) in the serine-threonine protein kinase active domain of the mature chain for TGFβR2 (PROSITE: PS00108; Pfam: PF00069, accessed 03/02/06). Genotyping TGFBR2: c.1149G>A did not reveal a significant association with diabetic nephropathy, however we did identify a doubling of the minor allele in cases (MAF: 1.9% in cases vs. 0.8% in controls). This finding may be due to the low frequency of minor allele, however our available sample numbers do not provide sufficient power to appropriately assess the association of this SNP with diabetic nephropathy. The search for causative variants for susceptibility to diabetic nephropathy is constrained by limited numbers of well-characterised, precisely phenotyped cases and controls, which represents a major challenge in the study of complex disease genetics. While the power to identify disease gene loci is influenced by many factors, the requirement for adequate samples sizes of stringently phenotyped individuals is critical to the success and validity of complex disease association studies. Our results warrant further investigations of rare variants, particularly the TGFBR2 exonic SNPs, provided the sample population is sufficiently powered to assess the association.

Conclusion

Although experimental evidence suggests TGFβ1 blockade may be an important therapeutic target we were unable to identify any association between TGFB1 gene variants and diabetic nephropathy. In resequencing the genes we identified eight novel variants for TGFB1, TGFBR1 and TGFBR2 genes but did not detect significant association between any of the common SNPs and nephropathy in this Caucasian population with type 1 diabetes.

Abbreviations

MAF

Minor allele frequency

SNP

Single nucleotide polymorphism

UTR

Untranslated region

TGF

Transforming growth factor

Declarations

Acknowledgements

This work was funded by the Research and Development Office of Northern Ireland and the Health Research Board of Ireland. A. J. McK is supported by a Northern Ireland Kidney Research Fund postdoctoral fellowship.

Authors’ Affiliations

(1)
Nephrology Research Group, Queen's University of Belfast
(2)
Epidemiology Research Groups, Queen's University of Belfast
(3)
Faculty of Life Sciences, University of Manchester
(4)
Conway Institute of Biomolecular and Biomedical Research, University College Dublin

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  41. Pre-publication history

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© McKnight et al; licensee BioMed Central Ltd. 2007

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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