Abstract
One-carbon metabolism mediates the inter-conversion of folates for the synthesis of precursors used in DNA synthesis, repair and methylation. Inadequate folate nutrition or compromised metabolism can disrupt these processes and facilitate carcinogenesis. In this study, we investigated associations of 39 candidate SNPs in nine one-carbon metabolism genes with risk of prostate cancer using 1,144 cases and 1,144 controls from the Cancer Prevention Study-II Nutrition Cohort. None of these SNPs were significantly associated with prostate cancer risk, either overall or in cases with advanced prostate cancer. Thus, our findings do not support the hypothesis that common genetic variation in one-carbon metabolism genes influences prostate cancer risk.
Perturbation in one-carbon metabolism caused by inadequate folate nutrition or genetic variation in the enzymes in this pathway can compromise the synthesis of DNA precursors, disturb DNA repair and methylation, and facilitate carcinogenesis. Disruption of these basic processes could potentially influence tumor development in any tissue. However, the only cancer for which an association with altered one-carbon metabolism has been consistently found to date is colorectal cancer (1, 2). A number of studies have examined whether risk of prostate cancer, the most frequent cancer among men in the U.S. (3), is affected by changes in folate nutrition or metabolism. The results of studies of dietary folate (4, 5, 6, 7), blood folate levels (8, 9, 10, 11), and common genetic variants in methylenetetrahydrofolate reductase (MTHFR) (12, 13, 14, 15, 16) have been mixed. In this study, we investigated the association of the genes MTHFR, methionine synthase (MTR), methionine synthase reductase (MTRR), cystathionine β-synthase (CBS), serine hydroxymethyltransferase (SHMT1), thymidine synthase (TYMS), dihydrofolate reductase (DHFR), methylenetetrahydrofolate dehydrogenase/methenyltetrahydrofolate cyclohydrolase/formyltetrahydrofolate synthase (MTHFD1), and formyltetrahydrofolate dehydrogenase (FTHFD) with prostate cancer using cases and controls nested in the American Cancer Society Cancer Prevention II (CPS-II) Nutrition Cohort.
Methods
Study Population
Prostate cancer cases and controls were participants in the CPS-II Nutrition Cohort, a prospective study of cancer incidence of approximately 184,000 U.S. adults begun in 1992. The recruitment and characteristics of this cohort have been described previously (17). Incident cases reported by response to follow-up questionnaires, which were sent to participants in 1997 and every two years afterwards, or by linkage with the National Death Index were verified through medical records or state cancer registries (17). Blood samples were collected from a subset of Nutrition Cohort participants (21,965 women and 17,411 men) between June 1998 and June 2001.
We identified 1,144 men with a blood sample who had been diagnosed with prostate cancer between 1992 and 2003 and had no previous history of cancer (except nonmelanoma skin cancer). An equal number of controls were matched to the cases on age (±6 months), race/ethnicity, and date of blood collection (±6 months) using risk set sampling (18). Among the cases, 272 men had aggressive prostate cancer, defined as prostate cancer with Gleason score ≥8, grades 3–4, or stage D at diagnosis, or who had prostate cancer as their underlying cause of death.
SNP Selection and Genotyping
SNPs were selected from the dbSNP or Celera databases in October, 2004 if they: 1) had a minor allele frequency (MAF) in Caucasians > 5%, and 2) caused changes in the amino acid sequence, or 3) had been previously found to be associated with disease. For some genes for which only one SNP was identified using these criteria, one or two additional SNPs for which only frequency information was available were added. Seven additional tagging SNPs were selected for the FTHFD gene using early HapMap data (Release 16, 3/1/2005) to allow haplotype analysis of this gene.
All SNPs were genotyped using TaqMan at Applied Biosystems, Inc. (Foster City, CA). The genotyping success rate was >96% and the genotype distributions of the controls for all SNPs were in Hardy-Weinberg equilibrium (p>0.01).
Statistical Analysis
The association with prostate cancer risk was evaluated using a per allele odds ratio (OR) determined using unconditional logistic regression in which a continuous variable for the number of minor alleles (0, 1, or 2) was entered into the regression model. All models were adjusted for age (single year categories), race (White, other), and date of blood draw (single year categories). Haplotypes for blocks defined through Haploview (19) were estimated using the expectation-maximization algorithm implemented in the TAGSNPS program (20).
Results
Details of the 39 one-carbon metabolism SNPs studied are listed in Table 1. Based on the per-allele ORs and related p-values shown in this table, which assume an additive genetic model, none of the SNPs were significantly associated with an altered risk of prostate cancer. Additionally, no significant association was seen when the analysis was restricted to advanced prostate cancer. To consider the possibility that some SNPs may act through a recessive model, we also assessed the association of the homozygous variant genotype with prostate cancer. Again, no statistically significant associations were found, either with all prostate cancer cases or with advanced prostate cancer cases.
Table 1.
Gene locations, resulting amino acid (AA) changes, minor allele frequencies, and associations with prostate cancer risk for the one-carbon metabolism gene SNPs investigated in this study.
| Gene/SNP | Location | AA Change | Minor Allele | Minor Allele Frequency |
OR (95% CI) * | p† | |
|---|---|---|---|---|---|---|---|
| Cases | Controls | ||||||
| MTHFR | |||||||
| rs2066470, T118C | Exon 2 | None | T | 210 (9.6) | 207 (9.5) | 1.01 (0.82, 1.23) | 0.94 |
| rs1801133, C677T | Exon 5 | Val → Ala | T | 739 (33.6) | 765 (34.6) | 0.96 (0.85, 1.09) | 0.56 |
| rs1801131, A1298C | Exon 8 | Ala → Glu | C | 728 (33.0) | 743 (33.5) | 0.97(0.86 1.10) | 0.64 |
| rs2274976 | Exon 12 | Gln → Arg | A | 95 (4.3) | 120 (5.4) | 0.78 (0.59, 1.03) | 0.08 |
| MTR | |||||||
| rs1806505 | Intron 13 | N/A‡ | T | 877 (39.6) | 856 (38.6) | 1.05 (0.93, 1.18) | 0.44 |
| rs1805087, A2756G | Exon 26 | Asp → Gly | G | 435 (19.9) | 430 (19.5) | 1.03 (0.89, 1.20) | 0.69 |
| rs1050993 | 3′ UTR | N/A‡ | A | 837 (37.8) | 880 (39.6) | 0.92 (0.82, 1.04) | 0.18 |
| MTRR | |||||||
| rs1801394, A66G | Exon 2 | Met → Ile | A | 1021 (46.1) | 1005 (45.5) | 1.02 (0.91, 1.15) | 0.70 |
| rs1532268 | Exon 5 | Leu → Ser | T | 815 (36.9) | 798 (36.0) | 1.04 (0.92, 1.17) | 0.54 |
| rs162036 | Exon 7 | Lys → Arg | G | 273 (12.4) | 251 (11.3) | 1.11 (0.92, 1.33) | 0.28 |
| rs10380 | Exon 14 | Tyr → His | T | 231 (10.4) | 221 (10.0) | 1.05 (0.86, 1.27) | 0.65 |
| CBS | |||||||
| rs234706, Y233Y | Exon 8 | None | A | 745 (33.7) | 780 (35.1) | 0.94 (0.83, 1.06) | 0.32 |
| rs1801181, C1261T | Exon 12 | None | T | 774 (36.9) | 739 (35.1) | 1.08 (0.95, 1.23) | 0.23 |
| SHMT1 | |||||||
| rs64333 | 5′ UTR | N/A‡ | A | 677 (30.7) | 636 (28.7) | 1.10 (0.97, 1.25) | 0.15 |
| rs2273028 | Intron 7 | N/A‡ | T | 725 (32.9) | 691 (31.2) | 1.08 (0.96, 1.23) | 0.22 |
| rs1979277, C1420T | Exon 12 | Leu → Phe | A | 702 (31.8) | 675 (30.6) | 1.06 (0.93, 1.20) | 0.39 |
| TYMS | |||||||
| rs502396 | Intron 1 | N/A‡ | C | 1078 (49.0) | 1057 (47.9) | 1.04 (0.93, 1.17) | 0.50 |
| rs1001761 | Intron 2 | N/A‡ | T | 1067 (49.3) | 1016 (47.0) | 1.09 (0.97, 1.23) | 0.15 |
| rs699517 | 3′ UTR | N/A‡ | T | 733 (33.2) | 693 (31.2) | 1.09 (0.96, 1.23) | 0.20 |
| DHFR | |||||||
| rs836821 | Intron 2 | N/A‡ | T | 552 (25.0) | 594 (26.8) | 0.91 (0.79, 1.04) | 0.16 |
| rs1677693 | Intron 3 | N/A‡ | A | 550 (25.0) | 581 (26.5) | 0.93 (0.81, 1.06) | 0.26 |
| rs1643638 | Intron 4 | N/A‡ | C | 547 (24.9) | 589 (26.6) | 0.92 (0.80, 1.05) | 0.20 |
| MTHFD1 | |||||||
| rs1076991 | 5′ UTR | N/A‡ | G | 1017 (46.1) | 1022 (46.5) | 0.98 (0.87, 1.11) | 0.78 |
| rs1950902, R134K | Exon 6 | Arg → Lys | T | 413 (18.7) | 411 (18.5) | 1.01 (0.87, 1.17) | 0.91 |
| rs2236225, R653Q | Exon 20 | Arg → Gln | T | 1039 (47.3) | 1006 (46.0) | 1.05 (0.93, 1.19) | 0.39 |
| rs2236224 | Intron 21 | N/A‡ | T | 919 (41.5) | 911 (41.0) | 1.02 (0.90, 1.15) | 0.78 |
| FTHFD (ALDH1L1) | |||||||
| rs7617733 | Intron 1 | N/A‡ | A | 379 (17.1) | 360 (16.2) | 1.06 (0.91, 1.24) | 0.46 |
| rs4646701 | Intron 2 | N/A‡ | A | 854 (38.7) | 868 (39.4) | 0.98 (0.86, 1.10) | 0.69 |
| rs1823213 | Intron 2 | N/A‡ | A | 737 (33.4) | 765 (34.5) | 0.96 (0.85, 1.09) | 0.50 |
| rs2276731 | Intron 4 | N/A‡ | C | 411 (18.7) | 418 (18.8) | 0.99 (0.85, 1.15) | 0.90 |
| rs10934751 | Intron 8 | N/A‡ | G | 1066 (48.1) | 1066 (48.0) | 1.00 (0.89, 1.13) | 0.94 |
| rs1965848 | Intron 8 | N/A‡ | T | 896 (40.7) | 906 (41.1) | 0.98 (0.87, 1.11) | 0.80 |
| rs2886059 | Exon 9 | Val → Phe | T | 357 (16.1) | 352 (15.9) | 1.01 (0.86, 1.19) | 0.88 |
| rs11923466 | Intron 9 | N/A‡ | C | 920 (42.1) | 911 (41.3) | 1.03 (0.91, 1.16) | 0.64 |
| rs2002287 | Intron 13 | N/A‡ | C | 766 (34.6) | 771 (34.8) | 0.99 (0.88, 1.12) | 0.88 |
| rs2365004 | Intron 14 | N/A‡ | A | 768 (34.6) | 773 (34.9) | 0.99 (0.87, 1.12) | 0.85 |
| rs6774437 | Intron 16 | N/A‡ | A | 1065 (48.0) | 1051 (47.3) | 0.97 (0.86, 1.09) | 0.65 |
| rs2290053 | Intron 18 | N/A‡ | A | 1085 (49.2) | 1099 (49.9) | 1.03 (0.91, 1.16) | 0.63 |
| rs1127717, A2380C | Exon 21 | Asp → Gly | G | 490 (22.2) | 452 (20.4) | 1.12 (0.97, 1.29) | 0.13 |
Per allele odds ratio, adjusted for gender, age, and draw date.
p for trend, adjusted for gender, age, and draw date.
N/A: non-applicable because SNP is not located in a coding region
The genotyped SNPs included seven tagging SNPs that defined 3 separate haplotype blocks in the FTHFD gene. None of the haplotype blocks (1: defined by rs2365004 and rs11923466, 2: defined by rs2886059, rs10934751, and rs2276731, 3: third was defined by rs1823213 and rs4646701), were associated with altered risk of all prostate cancer or advanced prostate cancer.
Discussion
This study is the first to investigate 9 one-carbon metabolism genes in prostate cancer and utilizes one of the largest study populations for this purpose to date. With 1,144 cases and 1,144 controls, this study has ≥80% power to detect odds ratios as low as 1.3 for SNPs with MAFs ≥ 25% and as low as 1.45 for SNPs with MAFs ≥ 10%. Thus, this study was adequately powered to detect associations with common genetic variants of the magnitude typically.
Our null findings are consistent with the results of all (12, 14, 15, 16) but one (13) of the previous studies. The study that reported a significant association of prostate cancer risk with the MTHFR C677T SNP was based on only 21 cases of prostate cancer (13). Besides the MTHFR gene, only two other genes in one-carbon metabolism have been investigated in relation to prostate cancer. Similar to our findings, neither the nonsynonymous A2756G SNP in MTR (12, 16) nor an insertion/deletion polymorphism in CBS (12) were significantly associated with altered prostate cancer risk.
Our findings of no significant association for 39 SNPs in 9 genes involved in one-carbon metabolism suggest that perturbations in the enzymes in this pathway have little or no effect on prostate cancer incidence. Coupled with previous null findings for folate intake (4, 6, 7) or blood levels (8, 11), these results argue that altered folate nutrition or metabolism do not contribute to risk for prostate cancer.
References
- 1.Sanjoaquin MA, Allen N, Couto E, et al. Folate Intake and colorectal cancer risk: A meta-analysis approach. Int J Cancer. 2005;113:825–8. doi: 10.1002/ijc.20648. [DOI] [PubMed] [Google Scholar]
- 2.Hubner RA, Muir KR, Liu J-F, et al. Folate metabolism polymorphisms influence risk of colorectal adenoma recurrence. Cancer Epidemiol Biomark Prevent. 2006;15:1607–13. doi: 10.1158/1055-9965.EPI-06-0274. [DOI] [PubMed] [Google Scholar]
- 3.Jemal A, Siegel R, Ward E, et al. Cancer Statistics, 2007. CA Cancer J Clin. 2007;57:43–66. doi: 10.3322/canjclin.57.1.43. [DOI] [PubMed] [Google Scholar]
- 4.Vlajinac HD, Marinkovic JM, Ilic MD, et al. Diet and prostate cancer: a case-control study. Eur J Cancer. 1997;33:101–7. doi: 10.1016/s0959-8049(96)00373-5. [DOI] [PubMed] [Google Scholar]
- 5.Pelucchi C, Galeone C, Talamini R, et al. Dietary folate and risk of prostate cancer in Italy. Cancer Epidemiol Biomark Prevent. 2005;14:944–8. doi: 10.1158/1055-9965.EPI-04-0787. [DOI] [PubMed] [Google Scholar]
- 6.Stevens VL, Rodriguez C, Pavluck AL, et al. Folate nutrition and prostate cancer incidence in a large cohort of US men. Am J Epidemiol. 2006;163:989–96. doi: 10.1093/aje/kwj126. [DOI] [PubMed] [Google Scholar]
- 7.Weinstein SJ, Stolzenberg-Solomon R, Pietinen P, et al. Dietary factors of one-carbon metabolism and prostate cancer risk. Am J Clin Nutr. 2006;84:929–35. doi: 10.1093/ajcn/84.4.929. [DOI] [PubMed] [Google Scholar]
- 8.Weinstein SJ, Hartman TJ, Stolzenberg-Solomon R, et al. Null association between prostate cancer and serum folate, vitamin B6, vitamin B12, and homocysteine. Cancer Epidemiol Biomark Prevent. 2003;12:1271–2. [PubMed] [Google Scholar]
- 9.Hultdin J, Van Guelpen B, Bergh A, et al. Plasma folate vitamin B12, and homocysteine and prostate cancer risk: A prospective study. Int J Cancer. 2005;113:819–24. doi: 10.1002/ijc.20646. [DOI] [PubMed] [Google Scholar]
- 10.Rossi E, Hung J, Beilby JP, et al. Folate levels and cancer morbidity and mortality: Prospective cohort study from Busselton, Western Australia. Ann Epidemiol. 2006;16:206–12. doi: 10.1016/j.annepidem.2005.03.010. [DOI] [PubMed] [Google Scholar]
- 11.Johansson M, Appleby PN, Allen NE, et al. Circulating concentrations of folate and vitamin B12 in relation to prostate cancer risk: results from the European prospective investigation into cancer and nutrition study. Cancer Epidemiol Biomarkers Prev. 2008;17:279–85. doi: 10.1158/1055-9965.EPI-07-0657. [DOI] [PubMed] [Google Scholar]
- 12.Kimura F, Franke KH, Steinhoff C, et al. Methyl group metabolism gene polymorphisms and susceptibility to prostatic carcinoma. The Prostate. 2000;45:225–31. doi: 10.1002/1097-0045(20001101)45:3<225::aid-pros4>3.0.co;2-7. [DOI] [PubMed] [Google Scholar]
- 13.Heijmans BT, Boer JMA, Suchiman HED, et al. A common variant of the methylenetetrahydrofolate reductase gene (1p36) is associated with an increased risk of cancer. Cancer Res. 2003;63:1249–53. [PubMed] [Google Scholar]
- 14.Cicek MS, Nock NL, Conti DV, et al. Relationship between methylenetetrahydrofolate reductase C677T and A1298C genotypes and haplotypes and prostate cancer risk and aggressiveness. Cancer Epidemiol Biomark Prevent. 2004;13:1331–8. [PubMed] [Google Scholar]
- 15.Johansson M, Van Guelpen B, Hultdin J, et al. The MTHFR 677C-->T polymorphism and risk of prostate cancer: results from the CAPs study. Cancer Causes Control. 2007;18:1169–74. doi: 10.1007/s10552-007-9055-z. [DOI] [PubMed] [Google Scholar]
- 16.Marchal C, Redondo M, Reyes-Engel A, et al. Association between polymorphisms of folate-metabolizing enzymes and risk of prostate cancer. European Journal of Surgical Oncology. 2008;34:805–10. doi: 10.1016/j.ejso.2007.09.008. [DOI] [PubMed] [Google Scholar]
- 17.Calle EE, Rodriguez C, Jacobs EJ, et al. The American Cancer Society Cancer Prevention Study II Nutrition Cohort. Cancer. 2002;94:2490–501. doi: 10.1002/cncr.101970. [DOI] [PubMed] [Google Scholar]
- 18.Rothman KJ, Greenland S. Modern Epidemiology. Baltimore: Lippincott, Williams and Wilkens; 1998. [Google Scholar]
- 19.Gabriel SB, Schaffner SF, Nguyen H, et al. The structure of haplotype blocks in the human genome. Science. 2002;296:2225–9. doi: 10.1126/science.1069424. [DOI] [PubMed] [Google Scholar]
- 20.Stram DO, Pearce CL, Bretsky P, et al. Modeling and E–M estimation of haplotype-specific relative risks from genotype data fro a case-control study of unrelated individuals. Human Hered. 2003;55:179–90. doi: 10.1159/000073202. [DOI] [PubMed] [Google Scholar]