| Title |
One-carbon metabolism gene polymorphisms and risk of non-Hodgkin lymphoma in Australia
|
|---|---|
| Published in |
Human Genetics, September 2007
|
| DOI | 10.1007/s00439-007-0431-2 |
| Pubmed ID | |
| Authors |
Kyoung-Mu Lee, Qing Lan, Anne Kricker, Mark P. Purdue, Andrew E. Grulich, Claire M. Vajdic, Jennifer Turner, Denise Whitby, Daehee Kang, Stephen Chanock, Nathaniel Rothman, Bruce K. Armstrong |
| Abstract |
Dysregulation of the one-carbon metabolic pathway, which controls nucleotide synthesis and DNA methylation, may promote lymphomagenesis. We evaluated the association between polymorphisms in one-carbon metabolism genes and risk of non-Hodgkin lymphoma (NHL) in a population-based case-control study in Australia. Cases (n = 561) and controls (n = 506) were genotyped for 14 selected single-nucleotide polymorphisms in 10 genes (CBS, FPGS, FTHFD, MTHFR, MTHFS, MTR, SHMT1, SLC19A1, TCN1, and TYMS). We also conducted a meta-analysis of all studies of Caucasian populations investigating the association between MTHFR Ex5+79C > T (a.k.a., 677C>T) and NHL risk. A global test of 13 genotypes was statistically significant for diffuse large B-cell lymphoma (DLBCL; P = 0.008), but not for follicular lymphoma (FL; P = 0.27) or all NHL (P = 0.17). The T allele at MTHFR Ex5+79 was marginally significantly associated with all NHL (OR = 1.25, 95% CI = 0.98-1.59) and DLBCL (1.36, 0.96-1.93). The T allele at TYMS Ex8+157 was associated with a reduced risk of FL (0.64, 0.46-0.91). An elevated risk of NHL was also observed among carriers of the G allele at FTHFD Ex21+31 (all NHL, 1.31, 1.02-1.69; DLBCL, 1.50, 1.05-2.14). A meta-analysis of 11 studies conducted in Caucasian populations of European origin (4,121 cases and 5,358 controls) supported an association between the MTHFR Ex5+79 T allele and increased NHL risk (additive model, P = 0.01). In conclusion, the results of this study suggest that genetic polymorphisms of one-carbon metabolism genes such as MTHFR and TYMS may influence susceptibility to NHL. |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 29% |
| Researcher | 2 | 10% |
| Student > Postgraduate | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 5 | 24% |
| Unknown | 2 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 33% |
| Medicine and Dentistry | 5 | 24% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Social Sciences | 2 | 10% |
| Business, Management and Accounting | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 2 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 June 2011.
All research outputs
#7,454,298
of 22,789,076 outputs
Outputs from Human Genetics
#933
of 2,953 outputs
Outputs of similar age
#25,019
of 70,859 outputs
Outputs of similar age from Human Genetics
#7
of 8 outputs
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