The authors have declared that no competing interests exist.
Conceived and designed the experiments: JEH CM JL. Performed the experiments: SR AS CM EJ LS. Analyzed the data: SR CM JL. Contributed reagents/materials/analysis tools: JL CM EJ LS JEH. Wrote the paper: JEH CM JL LS SR.
Increased dietary intake of Selenium (Se) has been suggested to lower prostate cancer mortality, but supplementation trials have produced conflicting results. Se is incorporated into 25 selenoproteins. The aim of this work was to assess whether risk of prostate cancer is affected by genetic variants in genes coding for selenoproteins, either alone or in combination with Se status. 248 cases and 492 controls from an EPIC-Heidelberg nested case-control study were subjected to two-stage genotyping with an initial screening phase in which 384 tagging-SNPs covering 72 Se-related genes were determined in 94 cases and 94 controls using the Illumina Goldengate methodology. This analysis was followed by a second phase in which genotyping for candidate SNPs identified in the first phase was carried out in the full study using Sequenom. Risk of high-grade or advanced stage prostate cancer was modified by interactions between serum markers of Se status and genotypes for rs9880056 in
The micronutrient Selenium (Se) is essential for human health and sub-optimal intake has been suggested to increase risk of various multifactorial diseases
The biological functions of Se are carried out primarily by selenoproteins which contain Se in the form of the amino acid selenocysteine
Selenocysteine incorporation into selenoproteins occurs during translation and requires proteins such as SECIS-binding protein 2 (SBP2)
As the selenoprotein family and selenoprotein biosynthesis pathway are well characterised, the aim of the present study was to investigate the association between SNPs throughout the genes encoding selenoproteins, factors essential for selenocysteine incorporation and related antioxidant proteins, Se status (as assessed by measurement of total serum Se, selenoprotein P (SePP) concentration and serum glutathione peroxidase (GPx3) activity) and prostate cancer risk in a European population with a Se status lower than that found in the USA. To achieve this aim, DNA samples from EPIC-Heidelberg, a prospective cohort study aiming to evaluate the association between dietary, lifestyle and metabolic factors and the risk of cancer, were genotyped and plasma samples analysed for plasma selenium status, selenoprotein P concentration and GPx activity. Previously, the samples had been analysed for six selenoprotein SNPs and rs1053040 in
The EPIC-Heidelberg study was designed to evaluate the association between dietary, lifestyle and metabolic factors and the risk of cancer. A random sample of the general population of Heidelberg, Germany, and surrounding communities was provided by the local registries and invited to participate. From 1994 to 1998, 11928 men (aged 40–64) and 13612 women (aged 35–64) were recruited, comprising 38% of those approached
Self-reported cases of prostate cancer were verified by examination of medical records or death certificates (C61, C63.8 and C63.9; International Classification of Diseases for Oncology, 2nd edition). Tumor grade information (Gleason histologic grade) was used to categorize cases as high-grade (Gleason score ≥7), low-grade (<7) or unknown. Advanced prostate cancer was defined as prostate cancer with a Gleason sum score ≥7, TNM staging score of T3/4, N1-3 or M1 or prostate cancer as underlying cause of death. During the 2nd and 3rd follow-up rounds questions addressed history of prostate cancer in 1st degree relatives and participation in prostate specific antigen (PSA) screening. Only those cases who participated in screening before the date of cancer diagnosis were coded as having a positive screening history. Similarly, only controls participating in screening before the date of diagnosis were classified as controls participating in prostate cancer screening. Samples for analysis during the initial screening phase of genotyping include advanced prostate cancer cases and one matched control per case.
Genomic DNA was extracted from buffy coat with FlexiGene Kit (Qiagen, Hilden, Germany) in accordance with the manufacturer’s instructions. DNA was stored at 4°C until use. A custom Illumina™ GoldenGate assay was designed for analysis of 384 candidate SNPs (tagSNPs and potential functional SNPs) in the selenoprotein and selenium pathway. Tag SNPs were selected, using Haploview 3.2, with a cutoff minimum minor allele frequency (MAF, in CEU population) of 0.05 and pairwise tagging (r2 = 1-0.8). To include promoter regions and SNPs in LD in neighboring genes, regions covering the coding region +/−2 to15 kbp beyond the 5′ and 3′ ends were used for the selection. Selected SNPs were then assessed for suitability for the Illumina™ GoldenGate genotyping platform, and the analysis was carried out on SNPs which were GoldeneGate validated or two-hit validated with scores >60%. The average call rate was >99%. The list of SNPs on the chip is presented in
Subsequently genotyping for selected SNPs (rs9880056 in
GPx activity was determined with Ransel RS 505 kits (Randox, Crumlin, UK), as described previously
Baseline characteristics of the study population are given as mean and standard deviation or percentages by case-control status. Serum Se and SePP concentrations as well as GPx3 activity were nearly normally distributed and are presented as mean and standard deviation.
Among healthy controls, Pearson correlation coefficients were computed for serum Se, SePP and GPx3 activity. Genotype frequencies for the selected polymorphisms were computed and deviations from Hardy-Weinberg equilibrium were determined by Chi2 test. Conditional logistic regression stratified by the matched case set was used to calculate odds ratios (OR) and 95% confidence intervals (CI) for the association of the SNPs with prostate cancer risk, using the frequent homozygous genotype wild type as reference category. As reported earlier
To evaluate potential effect modification of the association between serum Se concentration and prostate cancer risk by genotype, we calculated OR (and 95% CI) of prostate cancer for the continuous variables (serum Se, SePP and GPx) stratified by genotype with unconditional logistic regression adjusting for the matching variables (time of recruitment and 5-year age group). Additionally adjustments were made for family history of prostate cancer, participation in PSA screening, smoking status and vigorous physical activity. Due to small numbers in the homozygous mutant genotype we also combined the heterozygote and homozygote (mutant) categories. We tested for interaction by comparing the unconditional logistic regression model with and without crossproduct terms (of genotype and continuous Se variable) based on the likelihood ratio statistic. This analysis was repeated in the subgroups according to stage and grade of prostate cancer. All analyses were performed with SAS 9.1 (SAS Institute, Cary, USA).
Baseline characteristics of the study population have been presented previously
Genotyping was carried out in two phases. In the initial hypothesis-generating phase the sub-group of advanced prostate cancer cases (n = 94) and an equal number of matched controls were genotyped for 384 SNPs including functional SNPs in selenoprotein genes and tagging SNPs covering the 25 selenoprotein genes and factors important for selenoprotein biosynthesis (
In a second genotyping phase, the full nested case-control study (248 cases/492 controls) was genotyped for SNPs that showed a significant interaction with markers of Se status in the first, pathway analysis, stage (see above: SNPs in
Gene | RS number | Genotype | Control N | Case N | OR (95%CI) | p-value |
|
rs9880056 | TT | 256 | 122 | ||
TC | 207 | 105 | 1.07 (0.78, 1.47) | 0.68 | ||
CC | 29 | 21 | 1.51 (0.83, 2.77) | 0.18 | ||
TC/CC | 236 | 126 | 1.12 (0.83, 1.52) | 0.47 | ||
|
rs9605030 | CC | 377 | 184 | ||
CT | 104 | 61 | 1.18 (0.83, 1.68) | 0.36 | ||
TT | 11 | 3 | 0.54 (0.15, 1.97) | 0.35 | ||
CT/TT | 115 | 64 | 1.13 (0.80, 1.60) | 0.49 | ||
|
rs9605031 | CC | 272 | 128 | ||
CT | 185 | 98 | 1.12 (0.82, 1.53) | 0.48 | ||
TT | 35 | 22 | 1.32 (0.75, 2.33) | 0.34 | ||
CT/TT | 220 | 120 | 1.15 (0.85, 1.55) | 0.36 | ||
|
rs3211684 | TT | 436 | 218 | ||
GT | 54 | 28 | 1.03 (0.65, 1.66) | 0.89 | ||
GG | 2 | 2 | 2.01 (0.28, 14.27) | 0.49 | ||
GT/GG | 56 | 30 | 1.07 (0.67, 1.69) | 0.78 | ||
|
rs7310505 | CC | 310 | 149 | ||
CA | 161 | 88 | 1.14 (0.82, 1.57) | 0.43 | ||
AA | 21 | 11 | 1.09 (0.51, 2.32) | 0.83 | ||
CA/AA | 182 | 99 | 1.13 (0.83, 1.54) | 0.43 | ||
|
rs28665122 | CC | 365 | 192 | ||
CT | 121 | 53 | 0.84 (0.59, 1.20) | 0.34 | ||
TT | 6 | 3 | 0.98 (0.25, 3.93) | 0.98 | ||
CT/TT | 127 | 56 | 0.85 (0.60, 1.20) | 0.35 |
OR, 95% confidence interval (CI) and P values were calculated for each SNP analysed using logistic regression. For each SNP, ORs are presented with reference to the most frequent homozygous genotype.
Gene | RS number | Genotype | Cases/Controls | OR (95% CI) | p-value |
|
rs9880056 | ||||
TT | 121/254 | 0.94 (0.81, 1.07) | 0.34 | ||
TC/CC | 123/236 | 0.89 (0.77, 1.02) | 0.09 | ||
|
0.46 | ||||
|
rs9880056 | ||||
TT | 121/255 | 0.89 (0.61, 1.28) | 0.52 | ||
TC/CC | 126/236 | 0.78 (0.54, 1.12) | 0.17 | ||
|
0.63 | ||||
|
rs9880056 | ||||
TT | 122/256 | 0.93 (0.79, 1.10) | 0.39 | ||
TC/CC | 126/236 | 0.93 (0.79, 1.09) | 0.36 | ||
|
0.97 | ||||
|
rs9605030 | ||||
CC | 182/377 | 0.95 (0.85, 1.06) | 0.39 | ||
CT/TT | 62/113 | 0.86 (0.69, 1.08) | 0.19 | ||
|
0.18 | ||||
|
rs9605030 | ||||
CC | 184/376 | 0.87 (0.65, 1.16) | 0.34 | ||
CT/TT | 63/115 | 0.85 (0.49, 1.48) | 0.57 | ||
|
0.9 | ||||
|
rs9605030 | ||||
CC | 184/377 | 0.92 (0.80, 1.05) | 0.21 | ||
CT/TT | 64/115 | 0.96 (0.77, 1.19) | 0.72 | ||
|
0.44 | ||||
|
rs9605031 | ||||
CC | 127/272 | 0.99 (0.88, 1.12) | 0.90 | ||
CT/TT | 117/218 | 0.82 (0.69, 0.96) |
|
||
|
|
||||
|
rs9605031 | ||||
CC | 128/271 | 0.91 (0.66, 1.27) | 0.58 | ||
CT/TT | 119/220 | 0.75 (0.49, 1.14) | 0.18 | ||
|
0.58 | ||||
|
rs9605031 | ||||
CC | 128/272 | 0.95 (0.81, 1.11) | 0.52 | ||
CT/TT | 120/220 | 0.93 (0.79, 1.10) | 0.40 | ||
|
0.93 | ||||
|
rs3211684 | ||||
GT/GG | 29/56 | 0.97 (0.65, 1.44) | 0.87 | ||
TT | 215/434 | 0.92 (0.83, 1.02) | 0.12 | ||
|
0.65 | ||||
|
rs3211684 | ||||
GT/GG | 30/56 | 0.92 (0.32, 2.62) | 0.87 | ||
TT | 217/435 | 0.84 (0.64, 1.10) | 0.20 | ||
|
0.51 | ||||
|
rs3211684 | ||||
GT/GG | 30/56 | 0.99 (0.64, 1.55) | 0.971 | ||
TT | 218/436 | 0.93 (0.83, 1.05) | 0.27 | ||
P |
0.66 | ||||
|
rs7310505 | ||||
CC | 146/310 | 0.88 (0.78, 1.00) |
|
||
CA/AA | 98/180 | 1.03 (0.87, 1.22) | 0.72 | ||
|
0.06 | ||||
|
rs7310505 | ||||
CC | 149/310 | 0.84 (0.61, 1.14) | 0.26 | ||
CA/AA | 98/181 | 0.98 (0.62, 1.57) | 0.95 | ||
|
0.47 | ||||
|
rs7310505 | ||||
CC | 149/310 | 0.89 (0.77, 1.04) | 0.15 | ||
CA/AA | 99/182 | 1 (0.84, 1.19) | 0.97 | ||
|
0.16 | ||||
|
rs28665122 | ||||
CC | 188/363 | 0.95 (0.85, 1.06) | 0.33 | ||
CT/TT | 56/127 | 0.86 (0.68, 1.08) | 0.19 | ||
|
0.11 | ||||
|
rs28665122 | ||||
CC | 191/365 | 0.87 (0.66, 1.17) | 0.36 | ||
CT/TT | 56/126 | 0.73 (0.41, 1.29) | 0.27 | ||
|
0.3 | ||||
|
rs28665122 | ||||
CC | 192/365 | 0.97 (0.85, 1.11) | 0.64 | ||
CT/TT | 56/127 | 0.8 (0.61, 1.05) | 0.11 | ||
|
0.2 |
OR, 95% confidence interval (CI) and P values were calculated for each SNP analysed using logistic regression. OR adjusted for age group, family history of prostate cancer, participation in PSA testing, smoking status, and vigorous physical activity. Pinteraction = P value of test for interaction between genotype and serum selenium concentration per 10 mg/l, serum SePP concentration (mg/l) or serum GPx3 activity per 100 U/l.
Analysis of the data for the prostate cancer cases according to clinical parameters showed that within the study there were 69 advanced cases and 172 cases with localized disease, 90 individuals with high-grade tumours and 130 with low grade tumours. Regardless of markers of Se status, when tumour grade and disease stage were taken into account in the analysis there was a trend towards reduced risk of a high grade tumour in individuals carrying at least one T allele for rs28665122 in the gene
Advanced cases | Localized disease | High grade | Low grade | ||||||||
Gene | RS number | Genotype | OR(95%CI) | p-value | OR(95%CI) | p-value | OR(95%CI) | p-value | OR(95%CI) | p-value | |
|
rs9880056 | TT | 1 | 1 | 1 | 1 | |||||
TC/CC | 0.96 (0.54, 1.69) | 0.89 | 1.26 (0.87, 1.84) | 0.22 | 0.92 (0.55, 1.52) | 0.73 | 1.28 (0.84, 1.95) | 0.25 | |||
|
rs9605030 | CC | 1 | 1 | 1 | 1 | |||||
CT/TT | 1.4 (0.73, 2.69) | 0.31 | 0.98 (0.64, 1.49) | 0.91 | 1.19 (0.68, 2.08) | 0.53 | 0.88 (0.53, 1.45) | 0.61 | |||
|
rs9605031 | CC | 1 | 1 | 1 | 1 | |||||
CT/TT | 1.09 (0.61, 1.95) | 0.77 | 1.12 (0.78, 1.59) | 0.54 | 0.97 (0.59, 1.58) | 0.90 | 1.09 (0.71, 1.66) | 0.69 | |||
|
rs3211684 | TT | 1 | 1 | 1 | 1 | |||||
GT/GG | 1.07 (0.44, 2.64) | 0.88 | 1.09 (0.64, 1.87) | 0.7455 | 1.21 (0.52, 2.84) | 0.66 | 0.92 (0.50, 1.70) | 0.80 | |||
|
rs7310505 | CC | 1 | 1 | 1 | 1 | |||||
CA/AA | 1.13 (0.63, 2.03) | 0.69 | 1.13 (0.78, 1.63) | 0.53 | 1.18 (0.71, 1.93) | 0.52 | 0.9 (0.59, 1.39) | 0.64 | |||
|
rs28665122 | CC | 1 | 1 | 1 | 1 | |||||
CT/TT | 0.93 (0.50, 1.76) | 0.83 | 0.83 (0.54, 1.27) | 0.39 | 0.57 (0.31, 1.06) | 0.08 | 1.05 (0.66, 1.68) | 0.84 |
OR, 95% confidence interval (CI) and P values were calculated for each SNP analysed using logistic regression and stratified according to disease stage. For each SNP, ORs are presented with reference to the most frequent homozygous genotype.
Advanced stage | Localised disease | High grade | Low grade | ||||||||
Gene | RS number | Genotype | OR (95%CI) | p-value | OR (95%CI) | p-value | OR (95%CI) | p-value | OR (95%CI) | p-value | |
|
rs9880056 | ||||||||||
rs9880056 | TT | 0.94 (0.72, 1.23) | 0.64 | 0.93 (0.78, 1.10) | 0.39 | 1 (0.80, 1.24) | 1.00 | 0.9 (0.75, 1.10) | 0.31 | ||
rs9880056 | TC/CC | 0.67 (0.50, 0.89) |
|
0.97 (0.81, 1.16) | 0.76 | 0.76 (0.61, 0.94) |
|
1.03 (0.82, 1.29) | 0.80 | ||
|
0.09 | 0.91 |
|
0.42 | |||||||
|
rs9880056 | ||||||||||
rs9880056 | TT | 0.78 (0.38, 1.62) | 0.51 | 0.87 (0.55, 1.37) | 0.55 | 1.2 (0.68, 2.11) | 0.53 | 0.65 (0.38, 1.10) | 0.11 | ||
rs9880056 | TC/CC | 0.39 (0.16, 0.91) |
|
0.95 (0.61, 1.46) | 0.80 | 0.47 (0.26, 0.87) |
|
1.11 (0.67, 1.85) | 0.69 | ||
|
0.16 | 0.71 |
|
0.07 | |||||||
|
rs9880056 | ||||||||||
rs9880056 | TT | 0.78 (0.52, 1.16) | 0.22 | 0.96 (0.80, 1.15) | 0.64 | 1.02 (0.73, 1.43) | 0.91 | 0.84 (0.67, 1.06) | 0.14 | ||
rs9880056 | TC/CC | 0.85 (0.59, 1.21) | 0.36 | 0.94 (0.78, 1.13) | 0.48 | 0.79 (0.61, 1.02) | 0.08 | 0.98 (0.75, 1.27) | 0.87 | ||
|
0.42 | 0.93 | 0.13 | 0.33 | |||||||
|
rs9605030 | ||||||||||
rs9605030 | CC | 0.83 (0.68, 1.03) | 0.09 | 1 (0.87, 1.14) | 0.95 | 0.92 (0.77, 1.10) | 0.37 | 0.97 (0.83, 1.13) | 0.69 | ||
rs9605030 | CT/TT | 0.77 (0.41, 1.44) | 0.41 | 0.9 (0.68, 1.18) | 0.43 | 0.7 (0.45, 1.08) | 0.10 | 1.08 (0.74, 1.57) | 0.68 | ||
|
0.76 | 0.22 |
|
0.49 | |||||||
|
rs9605030 | ||||||||||
rs9605030 | CC | 0.53 (0.29, 0.95) |
|
0.98 (0.69, 1.40) | 0.93 | 0.74 (0.47, 1.18) | 0.21 | 0.92 (0.62, 1.37) | 0.69 | ||
rs9605030 | CT/TT | 0.56 (0.09, 3.66) | 0.55 | 1.01 (0.52, 1.95) | 0.99 | 0.95 (0.32, 2.76) | 0.92 | 0.8 (0.31, 2.08) | 0.65 | ||
|
0.44 | 0.86 | 0.74 | 0.84 | |||||||
|
rs9605030 | ||||||||||
rs9605030 | CC | 0.76 (0.54, 1.07) | 0.11 | 0.94 (0.81, 1.09) | 0.43 | 0.86 (0.67, 1.10) | 0.23 | 0.89 (0.74, 1.08) | 0.24 | ||
rs9605030 | CT/TT | 0.85 (0.47, 1.55) | 0.60 | 0.98 (0.76, 1.27) | 0.89 | 0.94 (0.61, 1.44) | 0.77 | 1.08 (0.77, 1.50) | 0.66 | ||
|
0.29 | 0.81 | 0.54 | 0.27 | |||||||
|
rs9605031 | ||||||||||
rs9605031 | CC | 0.87 (0.68, 1.10) | 0.24 | 1.03 (0.89, 1.19) | 0.70 | 0.94 (0.78, 1.14) | 0.53 | 1 (0.84, 1.20) | 0.96 | ||
rs9605031 | CT/TT | 0.72 (0.50, 1.04) | 0.08 | 0.87 (0.71, 1.06) | 0.17 | 0.73 (0.55, 0.97) |
|
0.98 (0.76, 1.26) | 0.85 | ||
|
0.68 |
|
|
0.63 | |||||||
|
rs9605031 | ||||||||||
rs9605031 | CC | 0.63 (0.32, 1.22) | 0.17 | 0.97 (0.65, 1.44) | 0.89 | 0.7 (0.42, 1.17) | 0.17 | 0.98 (0.63, 1.53) | 0.93 | ||
rs9605031 | CT/TT | 0.44 (0.15, 1.27) | 0.13 | 0.96 (0.58, 1.58) | 0.87 | 0.77 (0.38, 1.56) | 0.46 | 0.85 (0.45, 1.60) | 0.62 | ||
|
0.71 | 0.85 | 0.71 | 0.83 | |||||||
|
rs9605031 | ||||||||||
rs9605031 | CC | 0.86 (0.58, 1.26) | 0.44 | 0.95 (0.79, 1.14) | 0.60 | 0.88 (0.67, 1.16) | 0.38 | 0.9 (0.72, 1.12) | 0.35 | ||
rs9605031 | CT/TT | 0.83 (0.54, 1.26) | 0.38 | 0.96 (0.79, 1.17) | 0.72 | 0.89 (0.66, 1.20) | 0.45 | 0.97 (0.76, 1.23) | 0.78 | ||
|
0.79 | 0.82 | 0.66 | 0.71 | |||||||
|
rs3211684 | ||||||||||
|
rs3211684 | GT/GG | – – | – | 1.01 (0.63, 1.62) | 0.96 | – – | – | 0.97 (0.84, 1.12) | 0.66 | |
|
rs3211684 | TT | 0.84 (0.69, 1.02) | 0.08 | 0.96 (0.85, 1.08) | 0.50 | 0.89 (0.76, 1.04) | 0.13 | 1.33 (0.67, 2.64) | 0.42 | |
|
0.54 | 0.4 | 0.84 | 0.48 | |||||||
|
rs3211684 | ||||||||||
|
rs3211684 | GT/GG | – – | – | 1.18 (0.33, 4.21) | 0.80 | 0.72 (0.04, 13.53) | 0.83 | 0.91 (0.62, 1.33) | 0.62 | |
|
rs3211684 | TT | 0.6 (0.34, 1.04) | 0.07 | 0.94 (0.68, 1.29) | 0.70 | 0.75 (0.49, 1.14) | 0.18 | 0.45 (0.06, 3.39) | 0.44 | |
|
0.81 | 0.48 | 0.4 | 0.96 | |||||||
|
rs3211684 | ||||||||||
|
rs3211684 | GT/GG | – – | – | 0.96 (0.58, 1.60) | 0.89 | 0.49 (0.13, 1.85) | 0.29 | 0.92 (0.78, 1.09) | 0.34 | |
|
rs3211684 | TT | 0.85 (0.64, 1.12) | 0.24 | 0.95 (0.83, 1.08) | 0.43 | 0.94 (0.77, 1.14) | 0.51 | 1.02 (0.50, 2.05) | 0.97 | |
|
0.92 | 0.42 | 0.06 | 0.23 | |||||||
|
rs7310505 | ||||||||||
rs7310505 | CC | 0.72 (0.56, 0.93) |
|
0.96 (0.83, 1.11) | 0.58 | 0.83 (0.68, 1.02) | 0.07 | 0.95 (0.80, 1.13) | 0.57 | ||
rs7310505 | CA/AA | 0.99 (0.70, 1.40) | 0.95 | 1.02 (0.83, 1.25) | 0.83 | 0.95 (0.73, 1.23) | 0.71 | 1.01 (0.79, 1.30) | 0.91 | ||
|
|
0.54 | 0.28 | 0.41 | |||||||
|
rs7310505 | ||||||||||
rs7310505 | CC | 0.43 (0.21, 0.88) |
|
1.05 (0.72, 1.52) | 0.80 | 0.74 (0.44, 1.24) | 0.25 | 0.92 (0.61, 1.40) | 0.71 | ||
rs7310505 | CA/AA | 1.2 (0.41, 3.53) | 0.74 | 0.83 (0.47, 1.47) | 0.51 | 0.68 (0.32, 1.44) | 0.31 | 0.98 (0.45, 2.11) | 0.95 | ||
|
|
0.37 | 0.73 | 1.00 | |||||||
|
rs7310505 | ||||||||||
rs7310505 | CC | 0.88 (0.64, 1.22) | 0.45 | 0.9 (0.75, 1.08) | 0.25 | 0.96 (0.73, 1.26) | 0.76 | 0.84 (0.68, 1.04) | 0.11 | ||
rs7310505 | CA/AA | 0.78 (0.47, 1.29) | 0.34 | 1.03 (0.84, 1.26) | 0.77 | 0.83 (0.60, 1.15) | 0.26 | 1.11 (0.81, 1.52) | 0.51 | ||
|
0.93 | 0.18 | 0.36 |
|
|||||||
|
rs28665122 | ||||||||||
|
rs28665122 | CC | 0.86 (0.70, 1.05) | 0.14 | 1.01 (0.89, 1.15) | 0.90 | 0.9 (0.76, 1.06) | 0.22 | 1 (0.86, 1.18) | 0.97 | |
|
rs28665122 | CT/TT | 1.09 (0.53, 2.24) | 0.81 | 0.88 (0.68, 1.16) | 0.37 | 0.76 (0.50, 1.17) | 0.21 | 0.89 (0.65, 1.22) | 0.48 | |
|
0.48 | 0.08 | 0.16 | 0.22 | |||||||
|
rs28665122 | ||||||||||
|
rs28665122 | CC | 0.62 (0.34, 1.11) | 0.11 | 1.04 (0.73, 1.48) | 0.81 | 0.8 (0.51, 1.26) | 0.34 | 0.92 (0.61, 1.38) | 0.69 | |
|
rs28665122 | CT/TT | 1.24 (0.22, 7.17) | 0.81 | 0.85 (0.43, 1.66) | 0.63 | 0.46 (0.18, 1.21) | 0.12 | 0.91 (0.40, 2.08) | 0.82 | |
|
0.94 | 0.14 | 0.32 | 0.78 | |||||||
|
rs28665122 | ||||||||||
|
rs28665122 | CC | 0.91 (0.67, 1.22) | 0.52 | 0.99 (0.85, 1.15) | 0.89 | 0.95 (0.75, 1.20) | 0.68 | 0.91 (0.75, 1.10) | 0.33 | |
|
rs28665122 | CT/TT | 0.58 (0.26, 1.30) | 0.19 | 0.88 (0.63, 1.23) | 0.45 | 0.46 (0.24, 0.89) |
|
0.98 (0.67, 1.44) | 0.92 | |
|
0.12 | 0.2 | 0.22 | 0.94 |
Logistic regression adjusted for matching factors (age and time of blood collection) and family history of prostate cancer, participation in PSA testing, smoking status, and vigorous physical activity. Data was stratified according to disease stage. Pinteraction = P value of test for interaction between genotype and serum selenium concentration per 10 mg/l, serum SePP concentration (mg/l) or serum GPx3 activity per 100 U/l.
Analysis of the data taking both clinical parameters and measures of Se status into account showed consistent association of rs9880056 in the
Although previous work has suggested a possible inverse association between Se levels and risk of prostate cancer
The study involved analysis of samples from the EPIC-Heidelberg study and benefited from the availability of dietary and lifestyle data. However, the relatively small number of participants, particularly in the first phase of analysis, meant that the study was underpowered. Together with the lack of correction for multiple testing, this is a limitation that could lead to potential false positives that could have occurred by chance. However the strategy chosen here provides the opportunity to potentially identify new candidate functional SNPs and highlights the potential role of several selenoproteins in prostate function or prostate cancer etiology. Additionally, this approach reinforces previous observations
TR1 and TR2 proteins have major roles in regulation of redox signalling, whilst SelK has recently been reported to be an endoplasmic reticulum protein that is thought to play a role in the unfolded protein response and endoplasmic reticulum homeostasis
The association of SNPs in
Selenoprotein expression in response to Se supplementation has been found to vary between individuals and some of these effects have been attributed to genetic polymorphisms in selenoproteins
The lack of significant association of genotype for single SNPs in
Large-scale Se supplementation trials in the USA have given contradictory outcomes with regards to evidence for a relationship between lower Se intake and increased risk of prostate cancer
In conclusion, this study shows a significant interaction between serum markers of Se status and
Pathway-wise genotyping for SNPs in selenoprotein and related genes in control and prostate cancer patients from the EPIC-Heidelberg cohort. A custom chip was designed for genotyping across the whole pathway; the SNPs analysed and the corresponding genes are shown in the two left columns. Genotyping was carried out on 94 advanced cases and 94 control. Statistical evaluation of main effects of genetic variants on prostate cancer risk was carried out using either co-dominant and dominant models and data stratified for case set.
(DOC)