Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

118 SNPs of folate-related genes and risks of spina bifida and conotruncal heart defects

  • Gary M Shaw1, 4, 5Email author,
  • Wei Lu2,
  • Huiping Zhu2,
  • Wei Yang3,
  • Farren BS Briggs4,
  • Suzan L Carmichael3, 5,
  • Lisa F Barcellos4,
  • Edward J Lammer5 and
  • Richard H Finnell2
BMC Medical Genetics200910:49

DOI: 10.1186/1471-2350-10-49

Received: 22 October 2008

Accepted: 03 June 2009

Published: 03 June 2009

Abstract

Background

Folic acid taken in early pregnancy reduces risks for delivering offspring with several congenital anomalies. The mechanism by which folic acid reduces risk is unknown. Investigations into genetic variation that influences transport and metabolism of folate will help fill this data gap. We focused on 118 SNPs involved in folate transport and metabolism.

Methods

Using data from a California population-based registry, we investigated whether risks of spina bifida or conotruncal heart defects were influenced by 118 single nucleotide polymorphisms (SNPs) associated with the complex folate pathway. This case-control study included 259 infants with spina bifida and a random sample of 359 nonmalformed control infants born during 1983–86 or 1994–95. It also included 214 infants with conotruncal heart defects born during 1983–86. Infant genotyping was performed blinded to case or control status using a designed SNPlex assay. We examined single SNP effects for each of the 118 SNPs, as well as haplotypes, for each of the two outcomes.

Results

Few odds ratios (ORs) revealed sizable departures from 1.0. With respect to spina bifida, we observed ORs with 95% confidence intervals that did not include 1.0 for the following SNPs (heterozygous or homozygous) relative to the reference genotype: BHMT (rs3733890) OR = 1.8 (1.1–3.1), CBS (rs2851391) OR = 2.0 (1.2–3.1); CBS (rs234713) OR = 2.9 (1.3–6.7); MTHFD1 (rs2236224) OR = 1.7 (1.1–2.7); MTHFD1 (hcv11462908) OR = 0.2 (0–0.9); MTHFD2 (rs702465) OR = 0.6 (0.4–0.9); MTHFD2 (rs7571842) OR = 0.6 (0.4–0.9); MTHFR (rs1801133) OR = 2.0 (1.2–3.1); MTRR (rs162036) OR = 3.0 (1.5–5.9); MTRR (rs10380) OR = 3.4 (1.6–7.1); MTRR (rs1801394) OR = 0.7 (0.5–0.9); MTRR (rs9332) OR = 2.7 (1.3–5.3); TYMS (rs2847149) OR = 2.2 (1.4–3.5); TYMS (rs1001761) OR = 2.4 (1.5–3.8); and TYMS (rs502396) OR = 2.1 (1.3–3.3). However, multiple SNPs observed for a given gene showed evidence of linkage disequilibrium indicating that the observed SNPs were not individually contributing to risk. We did not observe any ORs with confidence intervals that did not include 1.0 for any of the studied SNPs with conotruncal heart defects. Haplotype reconstruction showed statistical evidence of nonrandom associations with TYMS, MTHFR, BHMT and MTR for spina bifida.

Conclusion

Our observations do not implicate a particular folate transport or metabolism gene to be strongly associated with risks for spina bifida or conotruncal defects.

Background

Periconceptional vitamin supplementation with folic acid substantially reduces risks of women having neural tube defect-affected pregnancies [1, 2] and has been implicated in reducing risks of several other congenital anomalies, including orofacial clefts and selected heart defects [311]. Mechanisms underlying these reduced risks have not been elucidated, although it has been speculated that supplementation with vitamins containing folic acid restores some normal developmental function that is genetically compromised in selected infants.

Investigating genetic variation that influences cellular absorption, transport, and metabolism of folate may offer insight into this unknown developmentally protective mechanism. Indeed, numerous investigations of genes that are specifically involved with folate metabolism have yielded at least one gene, 5, 10-methylenetetrahydrofolate reductase (MTHFR), that has been associated with a modest increased risk of neural tube defects (e.g., [1217]), and possibly heart defects [18, 19]. Observed risks with the two principal MTHFR variants, however, do not appear to account for a large proportion of the etiologic fraction of any of these defects, under the assumption that MTHFR variants have a causal role [17]. Thus, further investigation of other folate-related genes is necessary to reveal clues about mechanisms underlying the potential embryonic protective effects of folic acid supplementation.

We hypothesized that genetic susceptibility of fetal metabolism or transport of folate puts fetuses at risk for selected congenital anomalies. Using population-based data, we investigated 118 single nucleotide polymorphisms (SNPs) in 14 genes in the complex folate pathway as risk factors for spina bifida and conotruncal heart defects.

Methods

This population-based case-control study included infants with spina bifida or conotruncal heart defects diagnosed within 1 year after birth among infants and fetal deaths delivered to women residing in most California counties. Data were derived from the California Birth Defects Monitoring Program [20], a population-based active surveillance system for collecting information on infants and fetuses with congenital malformations. Diagnostic and demographic information was collected by program staff from multiple sources of medical records for all liveborn and stillborn fetuses (defined as >20 weeks gestation). Overall ascertainment for major malformations has been estimated as 97% complete [21]. Eligible were live born infants only because the source of DNA was from newborn screening cards.

Included were 259 infants with spina bifida and a random sample of 359 nonmalformed control infants born during 1983–86 and 1994–95 in selected counties in California. Also included for study were 214 infants with conotruncal heart defects, specifically d-transposition of the great arteries and tetralogy of Fallot. The random sample of 1983–86 controls for conotruncal heart defects included 220 of the overall 359. Newborn bloodspots were obtained from the State of California and their use in this study was consistent with the consent procedures at the time of sample collection. The protocol for this study was reviewed and approved by the State of California Health and Welfare Agency Committee for the Protection of Human Subjects.

Genomic DNA was extracted from dried blood spots on filter paper using the Puregene DNA Extraction Kit (Gentra, Minneapolis, MN). Prior to genotyping, genomic DNA was amplified using a commercial multiple displacement amplification (MDA) kit, GenomePhi (GE Healthcare, Piscataway, NJ). The MDA method relies on isothermal amplification using the DNA polymerase of the bacteriophage phi29 and is a recently developed technique for high performance WGA. MDA has been demonstrated to be reliable for genotyping, with the most favorable call rates, best genomic coverage, and lowest amplification bias [22]. Studies indicate no discernable difference between WGA samples with GenomiPhi kit and the original DNA templates [23, 24]. The whole genome amplification (WGA) product was then quantified using RNase P method (AppliedBiosystems, Foster City, CA). 150 ng WGA product was then used for each SNPlex assay pool which contained about 48 SNPs.

Genotype analyses were performed using SNPlex assays (AppliedBiosystems, Foster City, CA). SNP markers were selected using the SNPBrowser™ program (version 3.0) provided by AppliedBiosystems Inc. This program allowed selection of SNP markers from the HapMap database. For each target gene, tagging SNPs were selected based on the pairwise r2 > = 0.8. SNPs with minor allele frequencies lower than 10% in Caucasians were excluded. All validated non-synonymous SNPs were included. Successful rates for SNPlex assays were >96% for 75 SNPs, from 90% to 96% for 32 SNPs, from 70% to 90% for 7 SNPs. 15 SNPs suffered from more than 30% failure rates. In a subsequent effort to fill in the missing genotyping data and obtain higher call rate, we performed TaqMan SNP assays (Appliedbiosystems, Foster City, CA) for 22 of these SNPs on an ABI 7900 Genetic Analyzer.

All genotyping was performed blinded to subject's case or control status. Case and control infants were genotyped for 129 SNPs. Failure to obtain unambiguous genotype data on >50% of the samples for 11 SNPs (CBS rs1801181 and rs12329790; MTHFR rs1537514 and rs7533315; MTR rs10925257, NOS3 rs1800780 and hcv11631000; RFC1 rs1051266, rs4819130, hcv16186310, and rs7278825) resulted in their elimination from further analyses. The remaining 118 SNPs are shown in Table 1. The percentage of control study subjects (percentages were similar for cases) for whom genotype could be assigned is also shown in Table 1.
Table 1

Fourteen folate-related genes and 118 SNPs

Gene

Change

Chromosome

Base Position

SNP_ID

Type/Comment

Percent Genotyped1

BHMT

R (A/G)

5

78457715

rs3733890

exon, nonsynonymous R239Q

100

BHMT

Y (C/T)

5

78471967

rs1915706

Intergenic/Unknown

96.4

BHMT

(G/C)

5

78567093

rs1316753

Tag, BHMT

100

BHMT

M (C/A)

5

78465350

rs617219

intergenic

96.4

BHMT

M (A/C)

5

78438303

rs645112

Intergenic/Unknown

96.9

BHMT

W (A/T)

5

78462964

rs585800

untranslated region

94.2

BHMT

S (C/G)

5

78559288

rs3829809

Tag, BHMT

100

BHMT

Y (C/T)

5

78452172

rs567754

intron

95.8

BHMT2

M (A/C)

5

78400443

rs642431

intergenic-BHMT2;intron-DMGDH

91.1

BHMT2

R (A/G)

5

78405657

rs626105

intron

96.1

BHMT2

Y (C/T)

5

78409187

rs682985

exon, synonymous

95.5

BHMT2

M (A/C)

5

78387392

rs2253262

exon, synonymous

96.4

BHMT2

K(G/T)

5

78402082

rs670220

Validated

96.7

BHMT2

R (A/G)

5

78404048

rs592052

intron

99.2

BHMT2

R (A/G)

5

78419219

rs597560

intron

98.3

CBS

Y (T/C)

21

43360473

rs2851391

intron

92.5

CBS

R (A/G)

21

43359173

rs2298759

intron

72.4

CBS

Y (T/C)

21

43361102

rs234714

intron

90

CBS

S (C/G)

21

43346936

rs1051319

untranslated region

91.9

CBS

Y (T/C)

21

43376503

rs234784

Tag, CBS

99.7

CBS

N (A/C/G/T)

21

43346760

rs12613

untranslated region

92.5

CBS

S (C/G)

21

43377074

rs234785

Tag, CBS

100

CBS

R (A/G)

21

43360960

rs234713

intron

91.1

CBS

Y (C/T)

21

43376312

rs234783

Tag, CBS

100

DHFR

Y(C/T)

5

79986537

rs1650697

Validated nsSNP

92.2

DHFR

W(A/T)

5

79957572

rs12109877

Validated

94.2

DHFR

Y(C/T)

5

79987790

rs380691

Validated

95.5

DHFR

M(A/C)

5

79985331

rs1478834

Validated

96.4

DHFR

Y(C/T)

5

79966012

rs1643638

Validated

92.8

DHFR

M(A/C)

5

79961366

rs2618372

Validated

96.9

DHFR

R (A/G)

5

79980489

rs13161245

Validated

96.1

DHFR

Y(C/T)

5

79975899

rs1643650

Validated

94.7

DHFR

K(G/T)

5

79981467

rs836821

Validated

97.5

FOLR1

Y (C/T)

11

73373406

rs1540087

untranslated region

95.8

FOLR1

W (T/A)

11

73380857

rs11235462

Tag, FOLR1

100

FOLR1

R (A/G)

11

73372879

rs2071010

untranslated region

91.9

FOLR2

R (A/G)

11

73404256

rs2298444

intron

92.2

FOLR2

R (A/G)

11

73402049

rs514933

intron

100

FOLR2

W (A/T)

11

73401368

rs651646

untranslated region

100

MTHFD1

Y (C/T)

14

63984935

rs2236222

intron

95.5

MTHFD1

Y (C/T)

14

63978904

rs2236224

intron

97.8

MTHFD1

Y (C/T)

14

63952133

rs1950902

exon, nonsynonymous

90.5

MTHFD1

Y (C/T)

14

63978598

rs2236225

exon, nonsynonymous G1958A (R653Q)

100

MTHFD1

(T/A)

14

63999040

hCV11462908

Tag, MTHFD1

100

MTHFD1

R (A/G)

14

63957808

hCV11660794

intron

95.3

MTHFD1

R (A/G)

14

63988165

rs11849530

intron

95.8

MTHFD1

R (A/G)

14

63990418

rs1256146

intron

95

MTHFD1

Y (C/T)

14

63985918

rs10137921

exon, nonsynonymous

96.4

MTHFD1

Y (C/T)

14

63980547

rs1256142

intron

97.8

MTHFD2

Y (T/C)

2

74304595

rs11126426

Intergenic, Tag

100

MTHFD2

(T/A)

2

74280806

rs702465

Intergenic, Tag

96.7

MTHFD2

R (A/G)

2

74313429

rs1667599

Intergenic, Tag

100

MTHFD2

R (A/G)

2

74340847

rs1667627

Validated

96.1

MTHFD2

W (A/T)

2

74333849

rs828858

Intergenic, Tag

100

MTHFD2

(C/G)

2

74281605

rs702466

Intergenic, Tag

99.7

MTHFD2

R (A/G)

2

74372559

rs7571842

Intergenic, Tag

100

MTHFD2

R (A/G)

2

74348376

rs828903

Validated

94.4

MTHFR

R (A/G)

1

11801310

rs3737964

Validated

95.8

MTHFR

R (A/G)

1

11823734

rs535107

Intergenic, Tag

93.3

MTHFR

K(G/T)

1

11798240

rs1931226

Validated

96.9

MTHFR

R(A/G)

1

11780518

rs4846048

Validated

89.7

MTHFR

Y (C/T)

1

11796598

rs7525338

Validated

97.5

MTHFR

R (A/G)

1

11785193

rs2274976

exon, nonsynonymous

93

MTHFR

Y (C/T)

1

11792217

rs4846052

intron

96.9

MTHFR

Y (C/T)

1

11790644

rs1801133

exon, nonsynonymous C677T

99.4

MTHFR

R (A/G)

1

11775209

rs1889292

Intergenic, Tag

100

MTHFR

Y (C/T)

1

11797323

rs2066470

exon, synonymous

95.3

MTHFR

R (A/G)

1

11788723

rs4846051

exon, synonymous

93

MTHFR

R (A/G)

1

11786566

rs1476413

intron

93.9

MTHFR

M (A/C)

1

11788742

rs1801131

exon, nonsynonymous A1298C

99.7

MTR

M (A/C)

1

233374717

rs2275565

Validated

96.1

MTR

Y (C/T)

1

233322616

rs1806505

intron

97.5

MTR

K(G/T)

1

233386474

rs3820571

Validated

96.1

MTR

Y (C/T)

1

233335898

rs3754255

Validated

94.7

MTR

S(C/G)

1

233381346

rs10802569

Validated

96.1

MTR

R (A/G)

1

233376992

rs1266164

intron

96.1

MTR

R (A/G)

1

233374541

rs1805087

exon, nonsynonymous A2756G

96.4

MTR

W(A/T)

1

233385428

rs4659743

Validated

98.3

MTR

K(G/T)

1

233390667

rs6676866

Validated

98.3

MTR

S(C/G)

1

233315110

rs12060570

Validated

98.6

MTR

W(A/T)

1

233306545

rs955516

Validated

99.2

MTR

K (G/T)

1

233313831

rs4077829

intron

96.7

MTR

R (A/G)

1

233364202

rs1770449

intron

94.4

MTR

S (C/G)

1

233353709

rs3768139

intron

95.5

MTR

R (A/G)

1

233300165

rs4659724

intron

97.2

MTR

Y (C/T)

1

233327367

rs6668344

intron

96.4

MTR

R (A/G)

1

233367345

rs7367859

Validated

93.9

MTR

K (G/T)

1

233354605

rs3768142

Validated

96.1

MTR

Y (C/T)

1

233348403

rs10925252

Validated

96.9

MTR

R (A/G)

1

233380610

rs2229276

exon, synonymous

95

MTR

R (A/G)

1

233388346

rs1050993

untranslated region

97.2

MTRR

R (A/G)

5

7938959

rs162036

Validated nsSNP Lys/Arg

95.5

MTRR

S (C/G)

5

7944506

rs16879334

exon, nonsynonymous Pro/Arg

90

MTRR

R (G/A)

5

7950319

rs1802059

exon, synonymous

94.7

MTRR

R (G/A)

5

7942216

rs2287779

exon, synonymous

97.2

MTRR

R (A/G)

5

7927847

rs326120

intron

87.7

MTRR

Y (C/T)

5

7950191

rs10380

exon, nonsynonymous, His/Tyr

96.4

MTRR

R (A/G)

5

7923973

rs1801394

exon, nonsynonymous

96.7

MTRR

Y (C/T)

5

7953712

rs9332

UTR

92.2

MTRR

S (C/G)

5

7938907

rs10064631

exon, nonsynonymous

95

MTRR

W (A/T)

5

7931424

rs2303080

exon, nonsynonymous

96.1

MTRR

R (A/G)

5

7949511

rs3776455

intron

95

MTRR

R (A/G)

5

7931179

rs1532268

exon, nonsynonymous

95

MTRR

R (A/G)

5

7945310

rs162048

intron

98.6

NOS3

R (A/G)

7

150145737

rs891512

intron

86.6

NOS3

R (A/G)

7

150127591

rs1800779

untranslated region

87.5

NOS3

Y (C/T)

7

150148555

rs3918211

exon, synonymous

96.9

RFC1

K (G/T)

21

45761011

rs3788189

intron

81.1

RFC1

R (A/G)

21

45755537

rs12483377

Tag, RFC

100

RFC1

R (A/G)

21

45756112

rs2236484

Intron, Tag

98.6

RFC1

R (A/G)

21

45761386

rs3788190

Intron, Tag

91.1

RFC1

S (C/G)

21

45750430

rs10483080

intron

99.7

RFC1

Y (C/T)

21

45777720

rs2330183

intron

91.4

TYMS

Y (C/T)

18

652215

rs11540152

exon, nonsynonymous

95.8

TYMS

Y (C/T)

18

660414

rs2853532

intron

96.4

TYMS

R (A/G)

18

656371

rs2847149

intron

97.2

TYMS

Y (C/T)

18

652103

rs1001761

intron

98.9

TYMS

Y (C/T)

18

649236

rs502396

intron

97.8

1Percent of 359 controls genotyped for each SNP.

Abbreviations: BHMT = betaine homocysteine methyltransferase; BHMT2 betaine homocysteine methyltransferase-2; CBS = cystathione beta synthase; DHFR = dihydrofolate reductase; FOLR1 folate receptor 1; FOLR2 folate receptor 2; MTHFD1 = methylenetetrahydrofolate dehydrogenase 1; MTHFD2 = methylenetetrahydrofolate dehydrogenase 2; MTHFR = methylenetetrahydrofolate reductase; MTR = methionine synthase; MTRR = methionine synthase reductase; NOS3 = nitric oxide synthase; RFC1 = reduced folate carrier 1; TYMS = thymidylate synthase.

Genotypes among controls were analyzed to verify that their distributions fit Hardy-Weinberg expectations. Genotypes for each SNP were statistically consistent with Hardy-Weinberg expectations. Odds ratios and 95% confidence intervals (CI) were used to estimate risks. These measures were calculated using SAS software (version 9.1). Information on maternal race/ethnicity was obtained for case and control infants from California birth certificates. Logistic regression was used to compute risk estimates adjusted for maternal race/ethnicity (white Hispanic; white nonHispanic, and other). Analyses estimated defect risks (spina bifida or conotruncal heart defects) for each SNP assuming a recessive model, i.e., homozygous variant genotype compared to homozygous reference genotype and heterozygous variant genotype compared to homozygous reference genotype. In addition to single SNP-at-a-time analyses, we explored haplotype block analyses. Haplotype analyses were performed using Haploview version 3.32. Identified blocks were assessed with odds ratios.

Results

Numbers of case and control infants stratified by race/ethnicity are shown in Table 2. These data show the expected greater frequency of Hispanics in the spina bifida case group.
Table 2

Racial/ethnic percentages of malformed cases and non-malformed controls, California 1983–86 and 1994–95.

 

Spina Bifida

Conotruncal Heart

 

Cases

n = 259

%2

Controls

n = 359

%2

Cases

n = 214

%2

Controls

n = 2201

%2

Race/Ethnicity

    

White, Hispanic

50.6

31.5

17.8

18.6

White, nonHispanic

35.9

47.4

53.3

61.8

Other

12.0

20.6

26.2

18.6

1The number of controls born in the period 1983–86 among the 359 selected for the overall study period 1983–86 and 1994–95. The 220 represent the birth years of cases with conotruncal heart defects.

2Percentages may not equal 100 owing to missing data or rounding.

We examined risks for each of the 118 SNPs and for each of the two birth defect outcome (Additional file 1). Few odds ratios (ORs) revealed sizable departures from 1.0. Given the large number of comparisons (n = 472) we expected more ORs to be substantially different from 1.0 by chance. With respect to spina bifida, we observed ORs with confidence intervals that did not include 1.0 for the following SNPs (heterozygous or homozygous) relative to the reference genotype: BHMT (rs3733890) OR = 1.8 (1.1–3.1), CBS (rs2851391) OR = 2.0 (1.2–3.1); CBS (rs234713) OR = 2.9 (1.3–6.7); MTHFD1 (rs2236224) OR = 1.7 (1.1–2.7); MTHFD1 (hcv11462908) OR = 0.2 (0–0.9); MTHFD2 (rs702465) OR = 0.6 (0.4–0.9); MTHFD2 (rs7571842) OR = 0.6 (0.4–0.9); MTHFR (rs1801133) OR = 2.0 (1.2–3.1); MTRR (rs162036) OR = 3.0 (1.5–5.9); MTRR (rs10380) OR = 3.4 (1.6–7.1); MTRR (rs1801394) OR = 0.7 (0.5–0.9); MTRR (rs9332) OR = 2.7 (1.3–5.3); TYMS (rs2847149) OR = 2.2 (1.4–3.5); TYMS (rs1001761) OR = 2.4 (1.5–3.8); and TYMS (rs502396) OR = 2.1 (1.3–3.3). Each gene involving multiple SNP associations was investigated for linkage disequilibrium. Modest to strong evidence for linkage disequilibrium was observed for SNPs in each gene, i.e., D' ranged from 0.44 to 1.0 with all p values < 10-4. With respect to conotruncal heart defects, we did not observe any OR with a confidence interval that did not include 1.0.

We did not observe evidence to indicate that risk patterns were confounded by race/ethnicity groupings, i.e., observed ORs were not substantially altered after adjusting for maternal race/ethnicity (not shown, available from authors upon request).

Haplotypes, reconstructed for each gene based on studied SNPs, were explored to assess risks for each case group. A total of 77 of the 118 studied SNPs formed 17 haplotype blocks. As shown in Table 3, blocks for TYMS, MTHFR, BHMT, and MTR showed some evidence of nonrandom effects for spina bifida. For each of these haplotypes we observed decreased risk associated with the lower frequency haplotype relative to the most frequent haplotype. Similar to SNP analyses, haplotype analyses for conotruncal heart defects did not reveal evidence of nonrandom effects, with the exception of one haplotype block for MTR (Table 4).
Table 3

Haplotype associations with risks of spina bifida

Haplotype Block

Frequency

Odds Ratio (95% CI)

TYMS

  

CGC

0.500

REF

TAT

0.373

0.7 (0.6–0.9)

TAC

0.115

0.5 (0.3–0.7)

MTRR

  

ATTAGCAACAC

0.264

REF

ACTGGCAGTGT

0.213

1.4 (1.0–1.9)

ACTAGCAACGC

0.201

0.8 (0.6–1.1)

GCTAGCGGCGC

0.162

1.1 (0.7–1.5)

ACAAAGAGCGC

0.055

1.1 (0.7–1.9)

ACTAGCAGCGC

0.034

0.6 (0.3–1.3)

ACTAAGAGCGC

0.027

1.2 (0.6–2.6)

ACTGGCAGCGT

0.011

1.4 (0.5–4.1)

MTHFR*

  

GGG

0.656

REF

AGA

0.163

0.9 (0.6–1.2)

AGG

0.121

0.9 (0.6–1.2)

AAA

0.057

0.6 (0.3–1.0)

MTHFR**

  

TCCCA

0.368

REF

CCCCA

0.231

0.7 (0.5–0.9)

CTCTG

0.180

0.8 (0.6–1.1)

CTTCG

0.099

0.6 (0.4–0.9)

CTCCG

0.063

0.7 (0.5–1.2)

CTCCA

0.037

1.0 (0.5–1.8)

CBS

  

CG

0.889

REF

TC

0.055

1.2 (0.7–1.9)

CC

0.053

0.6 (0.3–1.0)

RFC1*

  

CG

0.856

REF

GG

0.079

1.1 (0.7–1.7)

GA

0.063

1.0 (0.6–1.6)

RFC1**

  

TG

0.486

REF

GA

0.463

0.9 (0.7–1.2)

GG

0.046

0.6 (0.3–1.0)

MTHFD1*

  

CT

0.486

REF

TC

0.429

1.3 (1.0–1.6)

CC

0.080

0.9 (0.6–1.4)

MTHFD1**

  

GT

0.825

REF

AA

0.167

0.9 (0.6–1.2)

FOLR2

  

TA

0.549

REF

AG

0.356

1.0 (0.8–1.3)

AA

0.093

1.0 (0.7–1.6)

MTHFD2*

  

TA

0.589

REF

CA

0.321

1.1 (0.9–1.4)

CG

0.089

1.1 (0.7–1.6)

MTHFD2**

  

TC

0.388

REF

TT

0.332

1.2 (0.9–1.5)

AT

0.276

1.0 (0.8–1.4)

BHMT2

  

GGGTCA

0.466

REF

TAACTC

0.219

1.0 (0.7–1.3)

GAGCTC

0.171

1.1 (0.8–1.6)

GAGTCA

0.091

1.0 (0.6–1.5)

GGGTCC

0.022

0.7 (0.3–1.7)

BHMT*

  

CAA

0.339

REF

TGA

0.326

0.7 (0.5–0.9)

CGT

0.172

0.7 (0.5–1.0)

CGA

0.158

0.9 (0.6–1.2)

BHMT**

  

AC

0.501

REF

CT

0.373

0.8 (0.7–1.1)

AT

0.120

0.9 (0.6–1.3)

DHFR

  

CTTACCA

0.402

REF

CTTACCG

0.390

0.9 (0.7–1.2)

ACCGAAA

0.201

0.9 (0.7–1.3)

MTR

  

AATCTTTCCTAGAGGGCTTGG

0.373

REF

GTGGCCCTGGGAAGAAGAGAT

0.262

1.0 (0.7–1.3)

GTGGCCCTCTAGGTGACTTGG

0.190

0.9 (0.7–1.3)

GTGGCCCTGGGGAGAAGAGAT

0.045

1.4 (0.8–2.5)

GTGGCCTTCTAGATGACTTGT

0.040

0.6 (0.3–1.2)

GTGGCCCTCGAAAGGAGTTGT

0.032

0.3 (0.1–0.6)

TYMSincluded rs1001761, rs2847149 and, rs2853532; MTRRincluded rs326120, rs1532268, rs2303080, rs162036, rs2287779, rs16879334, rs162048, rs3776455, rs10380

rs1802059, and rs9332; MTHFR* included rs1889292, rs2274976, and rs1476413; MTHFR** included rs1801133, rs4846052, rs2066470, rs3737964, and rs535107; CBSincluded rs12613 and rs 1051319; RFC1* included rs10483080 and rs12483377; RFC1** included rs3788189 and rs3788190; MTHFD1* included rs2236224 and rs1256142; MTHFD1** included rs1256146 and hcv11462908; FOLR2included rs651646 and rs514933; MTHFD2* included rs11126426 and rs1667599; MTHFD2** included rs828858 and rs1667627; BHMT2included rs670220, rs592052, rs626105, rs682985, rs597560, and rs645112; BHMT* included rs567754, rs3733890, and rs585800; BHMT** included rs617219 and rs1915706; DHFRincluded rs2618372, rs1643638, rs1643650, rs13161245, rs836821, rs1478834, and rs380691; MTRincluded rs4659724, rs955516, rs4077829, rs12060570, rs1806505, rs6668344, rs3754255, rs10925252, rs3768139, rs3768142, rs1770449, rs7367859, rs1805087, rs2275565, rs1266164, rs2229276, rs10802569, rs4659743, rs3820571, rs1050993, and rs6676866.

Table 4

Haplotype association with risks of conotruncal heart defects

Haplotype

Frequency

Odds Ratios (95% CI)

Block 19 ( MTR )

  

AATCTTTCCTAGAGGGCTTGG

0.354

REF

GTGGCCCTGGGAAGAAGAGAT

0.272

1.1 (0.7–1.5)

GTGGCCCTCTAGGTGACTTGG

0.189

1.2 (0.8–1.8)

GTGGCCTTCTAGATGACTTGT

0.048

1.5 (0.8–3.0)

GTGGCCCTCGAAAGGAGTTGT

0.035

1.0 (0.5–2.1)

GTGGCCCTGGGGAGAAGAGAT

0.021

0.9 (0.3–2.2)

GATCTTTCCTAGAGGGCTTGG

0.013

10.7 (1.4–84.8)

Block 19 included rs4659724, rs955516, rs4077829, rs12060570, rs1806505, rs6668344, rs3754255, rs10925252, rs3768139, rs3768142, rs1770449, rs7367859, rs1805087, rs2275565, rs1266164, rs2229276, rs10802569, rs4659743, rs3820571, rs1050993, and

rs6676866.

Haplotype analyses were stratified by race/ethnic background (Hispanic white and nonHispanic white). We observed evidence of a nonrandom haplotype association with TYMS for spina bifida and conotruncal heart defects among nonHispanic whites. Lack of evidence for other haplotypes that were observed overall was likely the result of smaller sample sizes from stratification.

Discussion

In this California population we found only modest evidence that polymorphisms in 14 folate-related genes contributed to risk of spina bifida. SNPs contributing risks were in BHMT, CBS, MTHFD1, MTHFD2, MTHFR, MTRR, and TYMS. Haplotype association analyses further identified TYMS and MTHFR as potential contributors to spina bifida risk. In general, however, most of these folate-related genes showed little evidence for a gene-only effect on risk of spina bifida, and even less, on risks of conotruncal heart defects.

The 14 genes studied here have been implicated in the complex metabolic cycle involving folate (e.g., [2527]). To our knowledge, this study contained the largest number of SNPs in folate-related genes interrogated as risk factors for human spina bifida or conotruncal heart defects. Previous studies have included some of the SNPs examined here. For example, Boyles and colleagues [28] studied 28 SNPs in 11 folate-related genes and found that only BHMT (rs3733890) was associated with increased spina bifida risk. This BHMT association is consistent with our findings that showed an odds ratio of 1.8 (1.1–3.1).

Many studies have explored MTHFR 677 (rs1801133) polymorphism. A range of risks, including no-effect, has been reported for this SNP relative to spina bifida. Botto and Yang [15] in a meta-analysis demonstrated a pooled odds ratio of 1.8 for spina bifida among infants homozygous for 677T. A few studies have also explored this 677 SNP in MTHFR as a risk factor for selected congenital heart defects, with most investigations finding no or little association [18, 19, 2931]. We did observe a 2-fold increased risk of spina bifida associated with this SNP for homozygous infants. Further, haplotype analyses showed some association for the MTHFR gene as well.

Methionine synthase (MTR) is a vitamin B12 dependent enzyme that is essential for the remethylation of homocysteine to methionine. The enzyme is required by cells for the essential accumulation of folate [32]. One particular SNP (A2756G; rs1805087) has been considerably investigated, with increased risks of NTDs reported in some studies [3335], but not in others [36, 37]. We did not find an increased risk for spina bifida or conotruncal heart defects associated with this SNP or any other SNP of MTR.

Cystathione beta synthase (CBS) is critical to the degradation of homocysteine to cysteine. Regulation of this pyridoxal phosphate-dependent enzyme catalyzes the hydroxyl group of serine with the thiolate of homocysteine [38]. The polymorphism in the CBS gene that has received the most study is a 68 bp insertion (844ins68), with predominantly no associations observed for NTDs [27]. This polymorphism was not investigated in the current study. We did observe, however, two CBS SNPs (rs2851391 and rs234713) that showed increased risks for spina bifida. Boyles et al [28], albeit using a different study design than ours, observed that these two SNPs were not differentially transmitted from parents of infants with spina bifida.

MTRR gene polymorphisms (particularly rs1801394) have been investigated as a risk factor for both spina bifida and congenital heart defects. Polymorphisms in MTRR could alter homocysteine levels because methionine synthase reductase participates in maintaining the vitamin B12-dependent conversion of homocysteine to methionine [32]. The most frequently studied MTRR polymorphism has been the 66A>G (rs1801394). This polymorphism in infants was associated with a 2.6-fold increased risk of spina bifida in an earlier study by us [33], it was associated with increased risk for spina bifida in another study only when vitamin B12 levels were low [39], or in combination with MTHFR CC genotype [35]. The polymorphism in mothers of infants with neural tube defects has been associated with increased risk in one study [40], but not in another study [41]. Recent work from the Netherlands has shown a lack of association between this polymorphism and risk for conotruncal heart defects [42] as well as no increased risks for a broader phenotypic group of heart defects [43]. In this study, the 66A>G polymorphism was not associated with increased risks for either spina bifida or conotruncal heart defects. We did observe, however, approximately 3-fold elevated risks for spina bifida associated with three other MTRR SNPs (rs162036, rs10380, and rs9332). The significance of these observations will have to be explored in future studies.

With respect to MTHFD1 and MTHFD2, two studies have demonstrated an association with one polymorphism (rs 2236225) in MTHFD1 and NTD risk. One study showed a 1.5-fold increase in risk of an NTD-affected pregnancy in Irish women who were homozygous AA [44], a finding that confirmed an earlier increased risk that was identified in Irish women. Another study showed a similar risk for Italian women as well as a 1.9-fold risk for infants with the AA genotype to have spina bifida [45]. For this particular SNP, we observed a similar magnitude of risk (OR = 1.6) for infants with the homozygous genotype, but the estimate was relatively imprecise. We did observe a modestly elevated spina bifida risk for individuals who were homozygous for another MTHFD1 SNP (rs2236224) and modestly lowered risks for three others (hcv11462908, rs702465, and rs7571842). These observations will need to be replicated in future studies.

Polymorphisms in the DHFR gene have not been well-studied for their role in risks of birth defects. Three studies have investigated a 19-bp deletion with mixed results [4648]. That particular polymorphism was not interrogated in the current study.

Our analyses did not show associations with SNPs in RFC1. Previous investigations of this gene have focused on a particular SNP, rs1051266, and have found mixed results [37, 41, 4953]. This particular SNP was not analyzed here as a result of too many samples failing to be genotyped for this SNP using the SNPlex platform.

Recent studies have focused on the importance of TYMS in the folate metabolic pathway, including associations between TYMS polymorphisms and folate levels [5456]. This folate-dependent enzyme catalyzes the reductive methylation of deoxyuridylate (dUMP) to thymidylate (dTMP), thereby playing a central role in DNA synthesis and repair by serving as the primary intracellular source of dTMP [54, 5759]. We previously [56] observed a 4-fold increased risk of spina bifida in nonHispanic white infants who had a polymorphism for a 28 bp insertion in the promoter region. This observation, however, was not replicated in a population from the northern UK [55]. This particular polymorphism was not interrogated in the current study. Three of the five TYMS SNPs (rs284179, rs1001761, and rs502396) investigated here showed elevated risks for spina bifida for both heterozygote or homozygote individuals. This finding and the corresponding haplotype finding (Table 3) will be important to explore in future studies.

The strengths of this study were: 1) it investigated the potential effects of a large number of folate pathway SNPs, as well as investigated haplotype associations; 2) it had population-based ascertainment of two case phenotypes and controls; and 3) it included cases and controls born before the US food supply was fortified with folic acid, thus we would expect a sizable proportion of cases to have been folate-responsive.

Conversely, our study was limited in its effect estimation owing to small sample sizes for some comparisons. For example, our study had 80% power to detect risks of 2.5 or more associated with genotypes that were observed in at least 4% of controls. Another potential limitation is the lack of information on maternal folate status. Our working hypothesis is that transient elevation in maternal serum folate from supplementation or dietary intake could prevent birth defects by overcoming metabolic inefficiencies or transport-related issues. Absence of information on low folate status would make it more difficult to find putative genotypes. It is also possible that the protective effect of folic acid relates to correction of a maternal metabolic defect, rather than the fetus. Our study was limited to infant genotype information. Thus, we were unable to investigate the potential effects of maternal genotype. As with any study that seeks to explore associations with a large number of genotypes, findings are subject to chance owing to multiple comparisons. As noted above, we conducted 472 analytic comparisons and thus expected more "statistically significant" findings to arise by chance alone. Further, our findings may have been influenced by uncontrolled confounding by population stratification undetectable in analyses stratified or adjusted by race/ethnicity [60, 61]. Lastly, the selected SNPs represent only a fraction of the potential variation of the studied genes. Thus, full gene coverage was not achieved even though a large number of SNPs was studied.

Conclusion

Despite compelling evidence that folate intake by women in early pregnancy substantially reduces risks of selected birth defects, the underlying mechanisms have not been elucidated. Our study attempted to determine genetic mechanisms responsible for folic acid's preventive effects. Our observations do not implicate a particular folate transport or metabolism gene to be strongly associated with risks for spina bifida or conotruncal defects. Although we explored a sizable number of polymorphic areas in these genes, we clearly did not capture all the genetic variation. Thus, these genes may continue to be candidates for further inquiry. Alternatively, the preventive role of folate may be via other biological mechanisms such as methylation of nonfolate-related genes that participate in the closure of the neural tube or the development of the heart.

Declarations

Acknowledgements

This research was supported by funds from the Centers for Disease Control and Prevention, Center of Excellence Award U50/CCU913241, by NIH/NHLBI R01 HL085859, and by NIH/NINDS R01 NS050249. We thank the California Department of Public Health Maternal Child and Adolescent Health Division for providing data for these analyses. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the California Department of Public Health.

Authors’ Affiliations

(1)
Department of Pediatrics, Division of Neonatal & Developmental Medicine, Stanford University School of Medicine
(2)
Institute of Biosciences and Technology, Texas A&M Health Science Center
(3)
California Research Division, March of Dimes, California Research Division
(4)
School of Public Health, University of California, Berkeley, School of Public Health
(5)
Children's Hospital Oakland Research Institute

References

  1. Prevention of neural tube defects: results of the Medical Research Council vitamin study. MRC Vitamin Study Research Group. Lancet. 1991, 338 (8760): 131-7. 10.1016/0140-6736(91)90133-A.
  2. Czeizel AE, Dudάs I: Prevention of the first occurrence of neural-tube defects by periconceptional vitamin supplementation. N Engl J Med. 1992, 327 (26): 1832-5.View ArticlePubMedGoogle Scholar
  3. Shaw GM, Lammer EJ, Wasserman CR, O'Malley CD, Tolarova MM: Risks of orofacial clefts in children born to women using multivitamins containing folic acid periconceptionally. Lancet. 1995, 346: 393-6. 10.1016/S0140-6736(95)92778-6.View ArticlePubMedGoogle Scholar
  4. Shaw GM, O'Malley CD, Wasserman CR, Tolarova MM, Lammer EJ: Maternal periconceptional use of multivitamins and reduced risk for conotruncal heart defects and limb deficiencies among offspring. Am J Med Genet. 1995, 59: 536-45. 10.1002/ajmg.1320590428.View ArticlePubMedGoogle Scholar
  5. Botto LD, Mulinare J, Erickson JD: Occurrence of congenital heart defects in relation to maternal multivitamin use. Am J Epidemiol. 2000, 151 (9): 878-84.View ArticlePubMedGoogle Scholar
  6. Czeizel AE, Tüth M, Rockenbauer M: Population-based case-control study of folic acid supplementation during pregnancy. Teratology. 1996, 53 (6): 345-51. 10.1002/(SICI)1096-9926(199606)53:6<345::AID-TERA5>3.0.CO;2-Z.View ArticlePubMedGoogle Scholar
  7. Werler MM, Hayes C, Louik C, Shapiro S, Mitchell AA: Multivitamin supplementation and risk of birth defects. Am J Epidemiol. 1999, 150 (7): 675-82.View ArticlePubMedGoogle Scholar
  8. Loffredo LC, Souza JM, Freitas JA, Mossey PA: Oral clefts and vitamin supplementation. Cleft Palate Craniofac J. 2001, 38 (1): 76-83. 10.1597/1545-1569(2001)038<0076:OCAVS>2.0.CO;2.View ArticlePubMedGoogle Scholar
  9. Itikala PR, Watkins ML, Mulinare J, Moore CA, Liu Y: Maternal multivitamin use and orofacial clefts in offspring. Teratology. 2001, 63 (2): 79-86. 10.1002/1096-9926(200102)63:2<79::AID-TERA1013>3.0.CO;2-3.View ArticlePubMedGoogle Scholar
  10. Czeizel AE: Reduction of urinary tract and cardiovascular defects by periconceptional multivitamin supplementation. Am J Med Genet. 1996, 62 (2): 179-83. 10.1002/(SICI)1096-8628(19960315)62:2<179::AID-AJMG12>3.0.CO;2-L.View ArticlePubMedGoogle Scholar
  11. Czeizel AE, Dobó M, Vargha P: Hungarian cohort-controlled trial of periconceptional multivitamin supplementation shows a reduction in certain congenital abnormalities. Birth Defects Res A Clin Mol Teratol. 2004, 70 (11): 853-61. 10.1002/bdra.20086.View ArticlePubMedGoogle Scholar
  12. Put van der NM, Steegers-Theunissen RP, Frosst P, Trijbels FJ, Eskes TK, Heuvel van den LP, Mariman EC, den Heyer M, Rozen R, Blom HJ: Mutated methylenetetrahydrofolate reductase as a risk factor for spina bifida. Lancet. 1995, 346 (8982): 1070-1. 10.1016/S0140-6736(95)91743-8.View ArticlePubMedGoogle Scholar
  13. Put van der NM, Heuvel van den LP, Steegers-Theunissen RP, Trijbels FJ, Eskes TK, Mariman EC, den Heyer M, Blom HJ: Decreased methylene tetrahydrofolate reductase activity due to the 677C-->T mutation in families with spina bifida offspring. J Mol Med. 1996, 74 (11): 691-4. 10.1007/s001090050073.View ArticlePubMedGoogle Scholar
  14. Kirke PN, Mills JL, Whitehead AS, Molloy A, Scott JM: Methylenetetrahydrofolate reductase mutation and neural tube defects. Lancet. 1996, 348 (9033): 1037-8. 10.1016/S0140-6736(05)64971-9.View ArticlePubMedGoogle Scholar
  15. Shaw GM, Rozen R, Finnell RH, Wasserman CR, Lammer EJ: Maternal vitamin use, genetic variations of infant methylene tetrahydrofolate reductase and risk for spina bifida. Am J Epidemiol. 1998, 148 (1): 30-7.View ArticlePubMedGoogle Scholar
  16. Posey DL, Khoury MJ, Mulinare J, Admas MJ, Ou CY: Is mutated MTHFR a risk factor for neural tube defects?. Lancet. 1996, 347 (9002): 686-7. 10.1016/S0140-6736(96)91236-2.View ArticlePubMedGoogle Scholar
  17. Botto LD, Yang Q: 5,10-Methylenetetrahydrofolate reductase gene variants and congenital anomalies: a HuGE review. Am J Epidemiol. 2000, 151 (9): 862-77.View ArticlePubMedGoogle Scholar
  18. Junker R, Kotthoff S, Vielhaber H, Halimeh S, Kosch A, Koch HG, Kassenböhmer R, Heineking B, Nowak-Göttl U: Infant methylenetetrahydrofolate reductase 677TT genotype is a risk factor for congenital heart disease. Cardiovas Res. 2001, 51 (2): 251-4. 10.1016/S0008-6363(01)00286-3.View ArticleGoogle Scholar
  19. Wenstrom KD, Johanning GL, Johnston KE, DuBard M: Association of the C677T methylenetetrahydrofolate reductase mutation and elevated homocysteine levels with congenital cardiac malformations. Am J Obstet Gynecol. 2001, 184 (5): 806-17. 10.1067/mob.2001.113845.View ArticlePubMedGoogle Scholar
  20. Croen LA, Shaw GM, Jensvold NJ, Harris JA: Birth defects monitoring in California: a resource for epidemiological research. Paediatr Perinat Epidemiol. 1991, 5 (4): 423-7. 10.1111/j.1365-3016.1991.tb00728.x.View ArticlePubMedGoogle Scholar
  21. Schulman J, Hahn JA: Quality control of birth defects registry data: a case study. Publ Health Rep. 1993, 108 (1): 91-8.Google Scholar
  22. Lovmar L, Syvänen AC: Multiple displacement amplification to create a long-lasting source of DNA for genetic studies. Hum Mutat. 2006, 27 (1): 603-14. 10.1002/humu.20341.View ArticlePubMedGoogle Scholar
  23. Holbrook JF, Stabley D, Sol-Church K: Exploring whole genome amplification as a DNA recovery tool for molecular genetic studies. J Biomol Tech. 2005, 16 (2): 125-33.PubMedPubMed CentralGoogle Scholar
  24. Bergen AW, Qi Y, Haque KA, Welch RA, Chanock SJ: Effects of DNA mass on multiple displacement whole genome amplification and genotyping performance. BMC Biotechnol. 2005, 5: 24-10.1186/1472-6750-5-24.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Fredicksen A, Meyer K, Ueland PM, Vollset SE, Grotmol T, Schneede J: Large-scale population-based metabolic phenotyping of thirteen genetic polymorphisms related to one-carbon metabolism. Human Mut. 2007, 28 (9): 856-65. 10.1002/humu.20522.View ArticleGoogle Scholar
  26. Piedrahita JA, Oetma B, Bennett GD, van Waes J, Kamen BA, Richardson J, Lacey SW, Anderson RG, Finnell RH: Mice lacking the folic-acid binding protein Folbp1 are defective in early embryonic development. Nat Genet. 1999, 23 (2): 228-32. 10.1038/13861.View ArticlePubMedGoogle Scholar
  27. Linden van der IJ, Afman LA, Heil SG, Blom HJ: Genetic variation in genes of folate metabolism and neural-tube defect risk. Proc Nutr Soc. 2006, 65 (2): 204-15.View ArticlePubMedGoogle Scholar
  28. Boyles AL, Billups AV, Deak KL, Siegel DG, Mehltretter L, Slifer SH, Bassuk AG, Kessler JA, Reed MC, Nijhout HF, George TM, Enterline DS, Gilbert JR, Speer MC, NTD Collaborative Group: Neural tube defects and folate pathway genes: family-based association tests of gene-gene and gene-environment interactions. Environ Health Perspect. 2006, 114 (10): 1547-52.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Hobbs CA, James SJ, Parsian A, Krakowiak PA, Jerrigan S, Greenhaw JJ, Lu Y, Cleves MA: Congenital heart defects and genetic variants in the methylenetetrahydrofolate reductase gene. J Med Genet. 2006, 43 (2): 162-6. 10.1136/jmg.2005.032656.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Shaw GM, Iovannisci DM, Yang W, Finnell RH, Carmichael SL, Cheng S, Lammer EJ: Risks of human conotruncal heart defects associated with 32 single nucleotide polymorphisms of selected cardiovascular disease-related genes. Am J Med Genet A. 2005, 138 (1): 21-6.View ArticlePubMedGoogle Scholar
  31. Storti S, Vittorini S, Lascone MR, Sacchelli M, Collavoli A, Ripoli A, Cocchi G, Biagini A, Clerico A: Association between 5,10-methylenetetrahydrofolate reductase C677T and A1298C polymorphisms and conotruncal heart defects. Clin Chem Lab Med. 2003, 41 (3): 276-80. 10.1515/CCLM.2003.043.View ArticlePubMedGoogle Scholar
  32. Deng L, Elmore CL, Lawrance AK, Matthews RG, Rozen R: Methionine synthase reductase deficiency results in adverse reproductive outcomes and congenital heart defects in mice. Mol Genet Metab. 2008, 94 (3): 336-42. 10.1016/j.ymgme.2008.03.004.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Zhu H, Wicker NJ, Shaw GM, Lammer EJ, Hendricks K, Suarez L, Canfield M, Finnell RH: Homocysteine remethylation enzyme polymorphisms and increased risks for neural tube defects. Mol Genet Metab. 2003, 78 (3): 216-21. 10.1016/S1096-7192(03)00008-8.View ArticlePubMedGoogle Scholar
  34. Doolin MT, Barbaux S, McDonnell M, Hoess K, Whitehead AS, Mitchell LE: Maternal genetic effects, exerted by genes involved in homocysteine remethylation, influence the risk of spina bifida. Am J Hum Genet. 2002, 71 (5): 1222-6. 10.1086/344209.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Guçant-Rodriguez RM, Rendeli C, Namour B, Venuti L, Romano A, Anello G, Bosco P, Debard R, Gçrard P, Viola M, Salvaggio E, Guçant JL: Transcobalamin and methionine synthase reductase mutated polymorphisms aggravate the risk of neural tube defects in humans. Neurosci Lett. 2003, 344 (3): 189-92. 10.1016/S0304-3940(03)00468-3.View ArticleGoogle Scholar
  36. De Marco P, Calevo MG, Moroni A, Arata L, Merello E, Finnell RH, Zhu H, Andreussi L, Cama A, Capra V: Study of MTHFR and MS polymorphisms as risk factors for NTD in the Italian population. J Hum Genet. 2002, 47 (6): 319-24. 10.1007/s100380200043.View ArticlePubMedGoogle Scholar
  37. O'Leary VB, Mills JL, Pangilinan F, Kirke PN, Cox C, Conley M, Weiler A, Peng K, Shane B, Scott JM, Parle-McDermott A, Molly AM, Brody LC, Members of the Birth Defects Research Group: Analysis of methionine synthase reductase polymorphisms for neural tube defects risk association. Mol Genet Metab. 2005, 85 (3): 220-7. 10.1016/j.ymgme.2005.02.003.View ArticlePubMedGoogle Scholar
  38. Banerjee R, Zou CG: Redox regulation and reaction mechanism of human cystathionine-B-synthase: a PLP-dependent hemesensor protein. Arch Biochem Biophys. 2005, 433 (1): 144-56. 10.1016/j.abb.2004.08.037.View ArticlePubMedGoogle Scholar
  39. Wilson A, Platt R, Wu Q, Leclerc D, Christensen B, Yang H, Gravel RA, Rozen R: A common variant in methionine synthase reductase combined with low cobalamin (vitamin B12) increases risk for spina bifida. Mol Genet Metab. 1999, 67 (4): 317-23. 10.1006/mgme.1999.2879.View ArticlePubMedGoogle Scholar
  40. Candito M, Rivet R, Herbeth B, Boisson C, Rudigoz RC, Luton D, Journel H, Oury JF, Rouv F, Saura R, Vernhet I, Gaucherand P, Muller F, Guidicelli B, Heckenroth H, Poulain P, Blayau M, Francannet C, Roszy KL, Brustiç C, Staccini P, Gçrard P, Fillion-Emery N, Guçant-Rodriguez RM, Van Obberghen E, Guçant JL: Nutritional and genetic determinants of vitamin B and homocysteine metabolisms in neural tube defects: a multicenter case-control study. Am J Med Genet Part A. 2008, 146A (9): 1128-33. 10.1002/ajmg.a.32199.View ArticlePubMedGoogle Scholar
  41. Relton CL, Wilding CS, Laffling AJ, Jonas PA, Burgess T, Binks K, Tawn EJ, Burn J: Low erythrocyte folate status and polymorphic variation in folate-related genes are associated with risk of neural tube defect pregnancy. Mol Genet Metabol. 2004, 81 (4): 273-81. 10.1016/j.ymgme.2003.12.010.View ArticleGoogle Scholar
  42. van Beynum IM, Kouwenberg M, Kapusta L, den Heijer M, Linden van der IJ, Daniels O, Blom HJ: MTRR 66A>G polymorphism in relation to congenital heart defects. Clin Chem Lab Med. 2006, 44 (11): 1317-23. 10.1515/CCLM.2006.254.View ArticlePubMedGoogle Scholar
  43. Verkleij-Hagoort AC, van Driel LM, Lindemans J, Isaacs A, Steegers EA, Helbing WA, Uitterlinden AG, Steegers-Theunissen RP: Genetic lifestyle factors related to the periconception vitamin B12 status and congenital heart defects: a Dutch case-control study. Mol Genet Metab. 2008, 94 (1): 112-9. 10.1016/j.ymgme.2007.12.002.View ArticlePubMedGoogle Scholar
  44. Parle-McDermott A, Kirke PN, Mills JL, Molloy AM, Cox C, O'Leary VB, Pangilinan F, Conley M, Cleary L, Brody LC, Scott JM: Confirmation of the R653Q polymorphism of the trifunctional C1-synthase enzyme as a maternal risk for neural tube defects in the Irish population. Eur J Hum Genet. 2006, 14 (6): 768-72. 10.1038/sj.ejhg.5201603.View ArticlePubMedGoogle Scholar
  45. De Marco P, Merello E, Calevo MG, Mascelli S, Raso A, Cama A, Capra V: Evaluation of a methylenetetrahydrofolate-dehydrogenase 1958>A polymorphism for neural tube defect risk. J Hum Genet. 2006, 51 (2): 98-103. 10.1007/s10038-005-0329-6.View ArticlePubMedGoogle Scholar
  46. Johnson WG, Stenroos ES, Spychala JR, Chatkupt S, Ming SX, Buyske S: New 19 bp deletion polymorphism in Intron-1 of dihydrofolate reductase (DHFR): a risk factor for spina bifida acting in mothers during pregnancy?. Am J Med Genet A. 2004, 124A (4): 339-45. 10.1002/ajmg.a.20505.View ArticlePubMedGoogle Scholar
  47. Parle-McDermott A, Pangilinan F, Mills JL, Kirke PN, Gibney ER, Troendle J, O'Leary VB, Molloy AM, Conley M, Scott JM, Brody LC: The 19-bp deletion polymorphism in Intron-1 of dihyrofolate reductase (DHFR) may decrease rather than increase risk for spina bifida in the Irish population. Am J Med Genet A. 2007, 143A (11): 1174-80. 10.1002/ajmg.a.31725.View ArticlePubMedGoogle Scholar
  48. Linden van der IJ, Nguyen U, Heil SG, Franke B, Vloet S, Gellekink H, den Heijer M, Blom HJ: Variation and expression of dihydrofolate reductase (DHFR) in relation to spina bifida. Mol Genet Met. 2007, 91 (1): 98-103. 10.1016/j.ymgme.2007.01.009.View ArticleGoogle Scholar
  49. Shaw GM, Lammer EJ, Zhu H, Baker MW, Neri E, Finnell RH: Maternal periconceptional vitamin use, genetic variation of infant reduced folate carrier (A80G), and risk of spina bifida. Am J Med Genet. 2002, 108 (1): 1-6. 10.1002/ajmg.10195.View ArticlePubMedGoogle Scholar
  50. Shaw GM, Zhu H, Lamer EJ, Yang W, Finnell RH: Genetic variation of infant reduced folate carrier (A80G) and risk of orofacial and conotruncal heart defects. Am J Epidemiol. 2003, 158 (8): 747-52. 10.1093/aje/kwg189.View ArticlePubMedGoogle Scholar
  51. Pei L, Zhu H, Ren A, Li Z, Hao L, Finnell RH, Li Z: Reduced folate carrier gene is a risk factor for neural tube defects in a Chinese population. Birth Defects Res A Clin Mol Teratol. 2005, 73 (6): 430-3. 10.1002/bdra.20130.View ArticlePubMedGoogle Scholar
  52. Pei L, Zhu H, Zhu J, Ren A, Finnell RH, Li Z: Genetic variation of infant reduced folate carrier (A80G) and risk of orofacial defects and congenital heart defects in China. Ann Epidemiol. 2006, 16 (5): 352-6. 10.1016/j.annepidem.2005.02.014.View ArticlePubMedGoogle Scholar
  53. De Marco P, Calevo MG, Moroni A, Merello E, Raso A, Finnell RH, Zhu H, Andreussi L, Cama A, Capra V: Reduced folate carrier polymorphism (80A-->G) and neural tube defects. Eur J Hum Genet. 2003, 11 (3): 245-52. 10.1038/sj.ejhg.5200946.View ArticlePubMedGoogle Scholar
  54. Trinh BN, Ong CN, Coetzee GA, Yu MC, Laird PW: Thymidylate synthase: a novel genetic determinant of plasma homocysteine and folate levels. Hum Genet. 2002, 111 (3): 299-302. 10.1007/s00439-002-0779-2.View ArticlePubMedGoogle Scholar
  55. Wilding CS, Relton CL, Sutton MJ, Jonas PA, Lynch SA, Tawn EJ, Burn J: Thymidylate synthase repeat polymorphisms and risk of neural tube defects in a population from the Northern United Kingdom. Birth Def Res A Clin Mol Teratol. 2004, 70 (7): 483-5. 10.1002/bdra.20038.View ArticleGoogle Scholar
  56. Volcik KA, Shaw GM, Zhu H, Lammer EJ, Laurent C, Finnell RH: Associations between polymorphisms within the thymidylate synthase gene and spina bifida. Birth Defects Res A Clin Mol Teratol. 2003, 67 (11): 924-8. 10.1002/bdra.10029.View ArticlePubMedGoogle Scholar
  57. Liu J, Schmitz JC, Lin X, Tai N, Yan W, Farrell M, Bailly M, Chen T, Chu E: Thymidylate synthase as a translational regulator of cellular gene expression. Biochim Biophys Acta. 2002, 1587 (2–3): 174-82.View ArticlePubMedGoogle Scholar
  58. Kawate H, Landis DM, Loeb LA: Distribution of mutations in human thymidylate synthase yielding resistance to 5-fluorodeoxyuridine. J Biol Chem. 2002, 277 (39): 36304-11. 10.1074/jbc.M204956200.View ArticlePubMedGoogle Scholar
  59. Ulrich CM, Bigler J, Bostick R, Fosdick L, Potter JD: Thymidylate synthase promoter polymorphism, interaction with folate intake, and risk of colorectal adenomas. Cancer Res. 2002, 62 (12): 3361-4.PubMedGoogle Scholar
  60. Thomas DC, Witte JS: Point: population stratification: a problem for case-control studies of candidate-gene associations?. Cancer Epidemiol Biomarkers Prev. 2002, 11 (6): 505-12.PubMedGoogle Scholar
  61. Wacholder S, Rothman N, Caporaso N: Counterpoint: bias from population stratification is not a major threat to the validity of conclusions from epidemiological studies of common polymorphisms and cancer. Cancer Epidemiol Biomarkers Prev. 2002, 11 (6): 513-20.PubMedGoogle Scholar
  62. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/10/49/prepub

Copyright

© Shaw et al; licensee BioMed Central Ltd. 2009

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.

Advertisement