Genetic variants in the MRPS30 region and postmenopausal breast cancer risk.
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ABSTRACT:
SUBMITTER: Huang Y
PROVIDER: S-EPMC3446269 | biostudies-literature | 2012 Mar
REPOSITORIES: biostudies-literature
Publications
Genetic variants in the MRPS30 region and postmenopausal breast cancer risk.
Huang Ying Y Ballinger Dennis G DG Dai James Y JY Peters Ulrike U Hinds David A DA Cox David R DR Beilharz Erica E Chlebowski Rowan T RT Rossouw Jacques E JE McTiernan Anne A Rohan Thomas T Prentice Ross L RL
Genome medicine 20120312 3
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Project description:BackgroundGenome-wide association studies have identified several genomic regions that are associated with breast cancer risk, but these provide an explanation for only a small fraction of familial breast cancer aggregation. Genotype by environment interactions may contribute further to such explanation, and may help to refine the genomic regions of interest.MethodsWe examined genotypes for 4,988 SNPs, selected from recent genome-wide studies, and four randomized hormonal and dietary interventions among 2,166 women who developed invasive breast cancer during the intervention phase of the Women's Health Initiative (WHI) clinical trial (1993 to 2005), and one-to-one matched controls. These SNPs derive from 3,224 genomic regions having pairwise squared correlation (r2) between adjacent regions less than 0.2. Breast cancer and SNP associations were identified using a test statistic that combined evidence of overall association with evidence for SNPs by intervention interaction.ResultsThe combined 'main effect' and interaction test led to a focus on two genomic regions, the fibroblast growth factor receptor two (FGFR2) and the mitochondrial ribosomal protein S30 (MRPS30) regions. The ranking of SNPs by significance level, based on this combined test, was rather different from that based on the main effect alone, and drew attention to the vicinities of rs3750817 in FGFR2 and rs7705343 in MRPS30. Specifically, rs7705343 was included with several FGFR2 SNPs in a group of SNPs having an estimated false discovery rate < 0.05. In further analyses, there were suggestions (nominal P < 0.05) that hormonal and dietary intervention hazard ratios varied with the number of minor alleles of rs7705343.ConclusionsGenotype by environment interaction information may help to define genomic regions relevant to disease risk. Combined main effect and intervention interaction analyses raise novel hypotheses concerning the MRPS30 genomic region and the effects of hormonal and dietary exposures on postmenopausal breast cancer risk.
| S-EPMC3218816 | biostudies-literature
Project description:Lung cancer is one of the malignant tumors, and genetic background is a risk factor in lung cancer that cannot be neglected. In this study, we aimed to find out the effect of MRPS30-DT and NINJ2 variants on lung cancer risk. In this study, the seven selected single-nucleotide polymorphisms (SNPs) of MRPS30-DT and NINJ2 were genotyped in 509 lung cancer patients and 501 healthy controls based on the Agena MassARRAY platform. Odds ratios and 95% confidence intervals were calculated by logistic regression analysis to evaluate association between gene polymorphisms and lung cancer risk. False-positive report probability was also used to assess false-positive results. Furthermore, the interaction between SNPs was analyzed by multifactor dimensionality reduction to predict lung cancer risk. We identified the genotype TA of rs16901963 (T < A) in MRPS30-DT as a protective factor against lung cancer, while rs16901963-TT was significantly associated with an increased risk of lung cancer. We also revealed that the effect of MRPS30-DT and NINJ2 variants on the risk of lung cancer was dependent on age, gender, smoking, and drinking status. In conclusion, this study first proved that MRPS30-DT and NINJ2 variants played important roles in affecting the susceptibility to lung cancer.
| S-EPMC9999113 | biostudies-literature
Project description:Variants in microRNA genes may affect their expression by interfering with the microRNA maturation process and may substantially contribute to the risk of breast cancer. Recent studies have identified miR-10b as an interesting candidate because of its close association with the metastatic behavior of breast cancer. However, the roles of miR-10b-related single nucleotide polymorphisms in breast cancer susceptibility remain unclear. This case-control study evaluated the associations between variants in the upstream transcription regulation region of miR-10b and the risk of breast cancer among Chinese women. Seven potentially functional SNPs were investigated using genotyping assays. The potential biological functions of the identified positive SNPs were further evaluated using in silico databases. We found that rs4078756, which was located at the promoter region of miR-10b, was significantly associated with breast cancer risk (rs4078756 AG/GG versus AA, adjusted odds ratio: 1.17, 95% confidence interval: 1.02-1.35). The other six single nucleotide polymorphisms exhibited negative associations. Based on the in silico prediction, rs4078756 potentially regulated miR-10b expression through promoter activation or repression. These findings indicate that a potentially functional SNP (rs4078756) in the promoter region of miR-10b may contribute to breast cancer susceptibility among Chinese women.
| S-EPMC5485289 | biostudies-literature
Project description:BackgroundWhile some factors of breast morphology, such as density, are directly implicated in breast cancer, the relationship between breast size and cancer is less clear. Breast size is moderately heritable, yet the genetic variants leading to differences in breast size have not been identified.MethodsTo investigate the genetic factors underlying breast size, we conducted a genome-wide association study (GWAS) of self-reported bra cup size, controlling for age, genetic ancestry, breast surgeries, pregnancy history and bra band size, in a cohort of 16,175 women of European ancestry.ResultsWe identified seven single-nucleotide polymorphisms (SNPs) significantly associated with breast size (p<5.10(-8)): rs7816345 near ZNF703, rs4849887 and (independently) rs17625845 flanking INHBB, rs12173570 near ESR1, rs7089814 in ZNF365, rs12371778 near PTHLH, and rs62314947 near AREG. Two of these seven SNPs are in linkage disequilibrium (LD) with SNPs associated with breast cancer (those near ESR1 and PTHLH), and a third (ZNF365) is near, but not in LD with, a breast cancer SNP. The other three loci (ZNF703, INHBB, and AREG) have strong links to breast cancer, estrogen regulation, and breast development.ConclusionsThese results provide insight into the genetic factors underlying normal breast development and show that some of these factors are shared with breast cancer. While these results do not directly support any possible epidemiological relationships between breast size and cancer, this study may contribute to a better understanding of the subtle interactions between breast morphology and breast cancer risk.
| S-EPMC3483246 | biostudies-literature
Project description:Several recent genome-wide association studies have identified genetic variants associated with breast cancer. However, how much these genetic variants may help advance breast cancer risk prediction based on other clinical features, like mammographic findings, is unknown. We conducted a retrospective case-control study, collecting mammographic findings and high-frequency/low-penetrance genetic variants from an existing personalized medicine data repository. A Bayesian network was developed using Tree Augmented Naive Bayes (TAN) by training on the mammographic findings, with and without the 22 genetic variants collected. We analyzed the predictive performance using the area under the ROC curve, and found that the genetic variants significantly improved breast cancer risk prediction on mammograms. We also identified the interaction effect between the genetic variants and collected mammographic findings in an attempt to link genotype to mammographic phenotype to better understand disease patterns, mechanisms, and/or natural history.
| S-EPMC3900221 | biostudies-literature
Project description:IntroductionBreast cancer in situ (BCIS) diagnoses, a precursor lesion for invasive breast cancer, comprise about 20 % of all breast cancers (BC) in countries with screening programs. Family history of BC is considered one of the strongest risk factors for BCIS.MethodsTo evaluate the association of BC susceptibility loci with BCIS risk, we genotyped 39 single nucleotide polymorphisms (SNPs), associated with risk of invasive BC, in 1317 BCIS cases, 10,645 invasive BC cases, and 14,006 healthy controls in the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). Using unconditional logistic regression models adjusted for age and study, we estimated the association of SNPs with BCIS using two different comparison groups: healthy controls and invasive BC subjects to investigate whether BCIS and BC share a common genetic profile.ResultsWe found that five SNPs (CDKN2BAS-rs1011970, FGFR2-rs3750817, FGFR2-rs2981582, TNRC9-rs3803662, 5p12-rs10941679) were significantly associated with BCIS risk (P value adjusted for multiple comparisons <0.0016). Comparing invasive BC and BCIS, the largest difference was for CDKN2BAS-rs1011970, which showed a positive association with BCIS (OR = 1.24, 95 % CI: 1.11-1.38, P = 1.27 x 10(-4)) and no association with invasive BC (OR = 1.03, 95 % CI: 0.99-1.07, P = 0.06), with a P value for case-case comparison of 0.006. Subgroup analyses investigating associations with ductal carcinoma in situ (DCIS) found similar associations, albeit less significant (OR = 1.25, 95 % CI: 1.09-1.42, P = 1.07 x 10(-3)). Additional risk analyses showed significant associations with invasive disease at the 0.05 level for 28 of the alleles and the OR estimates were consistent with those reported by other studies.ConclusionsOur study adds to the knowledge that several of the known BC susceptibility loci are risk factors for both BCIS and invasive BC, with the possible exception of rs1011970, a putatively functional SNP situated in the CDKN2BAS gene that may be a specific BCIS susceptibility locus.
| S-EPMC4487950 | biostudies-literature
Project description:BACKGROUNDGenetics of estrogen synthesis and breast cancer risk has been elusive. The 1245A→C missense-encoding polymorphism in HSD3B1, which is common in White populations, is functionally adrenal permissive and increases synthesis of the aromatase substrate androstenedione. We hypothesized that homozygous inheritance of the adrenal-permissive HSD3B1(1245C) is associated with postmenopausal estrogen receptor-positive (ER-positive) breast cancer.METHODSA prospective study of postmenopausal ER-driven breast cancer was done for determination of HSD3B1 and circulating steroids. Validation was performed in 2 other cohorts. Adrenal-permissive genotype frequency was compared between postmenopausal ER-positive breast cancer, the general population, and postmenopausal ER-negative breast cancer.RESULTSProspective and validation studies had 157 and 538 patients, respectively, for the primary analysis of genotype frequency by ER status in White female breast cancer patients who were postmenopausal at diagnosis. The adrenal-permissive genotype frequency in postmenopausal White women with estrogen-driven breast cancer in the prospective cohort was 17.5% (21/120) compared with 5.4% (2/37) for ER-negative breast cancer (P = 0.108) and 9.6% (429/4451) in the general population (P = 0.0077). Adrenal-permissive genotype frequency for estrogen-driven postmenopausal breast cancer was validated using Cambridge and The Cancer Genome Atlas data sets: 14.4% (56/389) compared with 6.0% (9/149) for ER-negative breast cancer (P = 0.007) and the general population (P = 0.005). Circulating androstenedione concentration was higher with the adrenal-permissive genotype (P = 0.03).CONCLUSIONAdrenal-permissive genotype is associated with estrogen-driven postmenopausal breast cancer. These findings link genetic inheritance of endogenous estrogen exposure to estrogen-driven breast cancer.FUNDINGNational Cancer Institute, NIH (R01CA236780, R01CA172382, and P30-CA008748); and Prostate Cancer Foundation Challenge Award.
| S-EPMC8564898 | biostudies-literature
Project description:Whether depression and antidepressant (AD) use might influence breast cancer risk is unclear, and these exposures have not been evaluated together in a single, prospective cohort study of breast cancer risk.Among 71,439 postmenopausal women in the Women's Health Initiative Observational Study (WHI-OS), we estimated multivariable-adjusted HRs for the independent and joint effects of depressive symptoms and AD use on breast cancer risk using Cox proportional hazards regression.When analyzed separately, neither depressive symptoms nor AD use at baseline were associated with a significantly increased risk of total breast cancer (HR = 0.96, 95% CI, 0.85-1.08; HR = 1.04, 95% CI, 0.92-1.20, respectively) or invasive breast cancer (HR = 0.98, 95% CI, 0.86-1.12; HR = 1.00, 95% CI, 0.86-1.16, respectively). Current AD use was associated with a borderline-significant increase of in situ breast cancer (HR = 1.30, 95% CI, 0.99-1.75) after adjustment for depressive symptoms; however, this relationship was attenuated after adjustment for mammographic screening (HR = 1.08, 95% CI, 0.76-1.51). No significant variation in total breast cancer risk was observed when the separate and joint effects of depressive symptoms and AD use were explored (P for interaction = 0.14).We found no evidence that either depression or AD use influences breast cancer risk. An elevated risk of in situ disease among AD users could not be ruled out, though is likely due to increased screening in this subgroup.Given the high prevalence of these exposures, these results may provide reassurance to the millions of women who are depressed and/or use ADs each year.
| S-EPMC5555234 | biostudies-other
Project description:IntroductionKnown prediction models for breast cancer can potentially by improved by the addition of mammographic density and common genetic variants identified in genome-wide associations studies known to be associated with risk of the disease. We evaluated the benefit of including mammographic density and the cumulative effect of genetic variants in breast cancer risk prediction among women in a Singapore population.MethodsWe estimated the risk of breast cancer using a prospective cohort of 24,161 women aged 50 to 64 from Singapore with available mammograms and known risk factors for breast cancer who were recruited between 1994 and 1997. We measured mammographic density using the medio-lateral oblique views of both breasts. Each woman's genotype for 75 SNPs was simulated based on the genotype frequency obtained from the Breast Cancer Association Consortium data and the cumulative effect was summarized by a genetic risk score (GRS). Any improvement in the performance of our proposed prediction model versus one containing only variables from the Gail model was assessed by changes in receiver-operating characteristic and predictive values.ResultsDuring 17 years of follow-up, 680 breast cancer cases were diagnosed. The multivariate-adjusted hazard ratios (95% confidence intervals) were 1.60 (1.22-2.10), 2.20 (1.65-2.92), 2.33 (1.71-3.20), 2.12 (1.43-3.14), and 3.27 (2.24-4.76) for the corresponding mammographic density categories: 11-20cm2, 21-30cm2, 31-40cm2, 41-50cm2, 51-60cm2, and 1.10 (1.03-1.16) for GRS. At the predicted absolute 10-year risk thresholds of 2.5% and 3.0%, a model with mammographic density and GRS could correctly identify 0.9% and 0.5% more women who would develop the disease compared to a model using only the Gail variables, respectively.ConclusionMammographic density and common genetic variants can improve the discriminatory power of an established breast cancer risk prediction model among females in Singapore.
| S-EPMC4581713 | biostudies-literature
Project description:Long non-coding RNA (lncRNA) steroid receptor RNA activator (SRA) has been identified to activate steroid receptor transcriptional activity and participate in tumor pathogenesis. This case-control study evaluated the association between two haplotype tagging SNPs (htSNPs) (rs10463297, rs801460) of the whole SRA sequence and breast cancer risk. We found that rs10463297 TC genotype significantly increased BC risk compared with CC genotype in both the codominant (TC vs. TT: OR=1.43, 95 % CI=1.02-2.00) and recessive (TC+CC vs. TT: OR=1.39, 95 % CI=1.01-1.92) genetic models. Both TC, TC + CC genotypes of rs10463297 and GA, AA, GA+AA genotypes of rs801460 were significantly associated with estrogen receptor (ER) positivity status. rs10463297 TC (2.09 ± 0.41), CC (2.42 ± 0.51) and TC + CC (2.20 ± 0.47) genotypes were associated with higher blood plasma SRA mRNA levels compared with the TT genotype (1.45 ± 0.34). Gene-reproductive interaction analysis presented a best model consisted of four factors (rs10463297, age, post-menopausal, No. of pregnancy), which could increase the BC risk with 1.58-fold (OR=1.58, 95 % CI=1.23-2.03). These findings suggest that SRA genetic variants may contribute to BC risk and have apparent interaction with reproductive factors in BC progression.
| S-EPMC5008375 | biostudies-literature