The associations between a polygenic score, reproductive and menstrual risk factors and breast cancer risk

The Parkinson's-disease-associated mutation LRRK2-G2019S alters dopaminergic differentiation dynamics via NR2F1

Increasing evidence suggests that neurodevelopmental alterations might contribute to increase the susceptibility to develop neurodegenerative diseases. We investigate the occurrence of developmental abnormalities in dopaminergic neurons in a model of Parkinson's disease (PD). We monitor the differentiation of human patient-specific neuroepithelial stem cells (NESCs) into dopaminergic neurons. Using high-throughput image analyses and single-cell RNA sequencing, we observe that the PD-associated LRRK2-G2019S mutation alters the initial phase of neuronal differentiation by accelerating cell-cycle exit with a concomitant increase in cell death. We identify the NESC-specific core regulatory circuit and a molecular mechanism underlying the observed phenotypes. The expression of NR2F1, a key transcription factor involved in neurogenesis, decreases in LRRK2-G2019S NESCs, neurons, and midbrain organoids compared to controls. We also observe accelerated dopaminergic differentiation in vivo in NR2F1-deficient mouse embryos. This suggests a pathogenic mechanism involving the LRRK2-G2019S mutation, where the dynamics of dopaminergic differentiation are modified via NR2F1.

Discovery of breast cancer risk genes and establishment of a prediction model based on estrogen metabolism regulation

Background

Multiple common variants identified by genome-wide association studies have shown limited evidence of the risk of breast cancer in Chinese individuals. In this study, we aimed to uncover the relationship between estrogen levels and the genetic polymorphism of estrogen metabolism-related enzymes in breast cancer (BC) and establish a risk prediction model composed of estrogen-metabolizing enzyme genes and GWAS-identified breast cancer-related genes based on a polygenic risk score.

Methods

Unrelated BC patients and healthy subjects were recruited for analysis of estrogen levels and single nucleotide polymorphisms (SNPs) in genes encoding estrogen metabolism-related enzymes. The polygenic risk score (PRS) was used to explore the combined effect of multiple genes, which was calculated using a Bayesian approach. An independent sample t-test was used to evaluate the differences between PRS scores of BC and healthy subjects. The discriminatory accuracy of the models was compared using the area under the receiver operating characteristic (ROC) curve.

Results

The estrogen homeostasis profile was disturbed in BC patients, with parent estrogens (E1, E2) and carcinogenic catechol estrogens (2/4-OHE1, 2-OHE2, 4-OHE2) significantly accumulating in the serum of BC patients. We then established a PRS model to evaluate the role of SNPs in multiple genes. PRS model 1 (M1) was established from SNPs in 6 GWAS-identified high risk genes. On the basis of M1, we added SNPs from 7 estrogen metabolism enzyme genes to establish PRS model 2 (M2). The independent sample t-test results showed that there was no difference between BC and healthy subjects in M1 (P = 0.17); however, there was a significant difference between BC and healthy subjects in M2 (P = 4.9*10^− 5). The ROC curve results showed that the accuracy of M2 (AUC = 62.18%) in breast cancer risk identification was better than that of M1 (AUC = 54.56%).

Conclusion

Estrogen and related metabolic enzyme gene polymorphisms are closely related to BC. The model constructed by adding estrogen metabolic enzyme gene SNPs has a good predictive ability for breast cancer risk, and the accuracy is greatly improved compared with that of the PRS model that only includes GWAS-identified gene SNPs.

Genetic Variation and Hot Flashes: A Systematic Review

CONTEXT

Approximately 70% of women report experiencing vasomotor symptoms (VMS, hot flashes and/or night sweats). The etiology of VMS is not clearly understood but may include genetic factors.

EVIDENCE ACQUISITION

We searched PubMed and Embase in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. We included studies on associations between genetic variation and VMS. We excluded studies focused on medication interventions or prevention or treatment of breast cancer.

EVIDENCE SYNTHESIS

Of 202 unique citations, 18 citations met the inclusion criteria. Study sample sizes ranged from 51 to 17 695. Eleven of the 18 studies had fewer than 500 participants; 2 studies had 1000 or more. Overall, statistically significant associations with VMS were found for variants in 14 of the 26 genes assessed in candidate gene studies. The cytochrome P450 family 1 subfamily A member 1 (CYP1B1) gene was the focus of the largest number (n = 7) of studies, but strength and statistical significance of associations of CYP1B1 variants with VMS were inconsistent. A genome-wide association study reported statistically significant associations between 14 single-nucleotide variants in the tachykinin receptor 3 gene and VMS. Heterogeneity across trials regarding VMS measurement methods and effect measures precluded quantitative meta-analysis; there were few studies of each specific genetic variant.

CONCLUSIONS

Genetic variants are associated with VMS. The associations are not limited to variations in sex-steroid metabolism genes. However, studies were few and future studies are needed to confirm and extend these findings.

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.

Evaluation of significant genome-wide association studies risk - SNPs in young breast cancer patients

Purpose

Genome-wide-association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. Most of these studies were conducted primarily in postmenopausal breast cancer patients. Therefore, we set out to assess whether or not these breast cancer variants are also associated with an elevated risk of breast cancer in young premenopausal patients.

Methods

In 451 women of European ancestry who had prospectively enrolled in a longitudinal cohort study for women diagnosed with breast cancer at or under age 40, we genotyped 44 SNPs that were previously associated with breast cancer risk. A control group was comprised of 1142 postmenopausal healthy women from the Nurses’ Health Study (NHS). We assessed if the frequencies of the adequately genotyped SNPs differed significantly (p≤0.05) between the cohort of young breast cancer patients and postmenopausal controls, and then we corrected for multiple testing.

Results

Genotyping of the controls or cases was inadequate for comparisons between the groups for seven of the 44 SNPs. 9 of the remaining 37 were associated with breast cancer risk in young women with a p-value <0.05: rs10510102, rs1219648, rs13387042, rs1876206, rs2936870, rs2981579, rs3734805, rs3803662 and rs4973768. The directions of these associations were consistent with those in postmenopausal women. However, after correction for multiple testing (Benjamini Hochberg) none of the results remained statistically significant.

Conclusion

After correction for multiple testing, none of the alleles for postmenopausal breast cancer were clearly associated with risk of premenopausal breast cancer in this relatively small study.

Effect of Interaction between Early Menarche and Genetic Polymorphisms on Triglyceride

Early menarche has been associated with increased risk of metabolic syndrome. Therefore, investigating the association of each component of metabolic syndrome with age at menarche, and interactions between them, might lead to a better understanding of metabolic syndrome pathogenesis. In this study, we evaluated age at menarche for risk of metabolic syndrome and associations with its components. As a result, the risk of MetS incidence was significantly increased only at ≤12 years of age at menarche (OR = 1.91, P < 0.05). Women with early menarche (≤12 years) had significantly higher levels of triglycerides (β coefficient = 37.83, P = 0.02). In addition, hypertriglyceridemia was significantly increased at early menarche with 1.99 (95% CI: 1.16–3.41, P < 0.01). With GWAS-based pathway analysis, we found the type 2 diabetes mellitus, stress-activated protein kinase signaling, and Jun amino-terminal kinase cascade pathways (all nominal P < 0.001, all FDR < 0.05) to be significantly involved with early menarche on triglyceride levels. These findings may help us understand the role of early menarche on triglyceride and interaction between gene and early menarche on triglyceride for the development of metabolic syndrome.

Genetic variants associated with earlier age at menopause increase the risk of cardiovascular events in women

OBJECTIVE

To better understand the relationship between cardiovascular disease risk and age-at-natural menopause using genetic data.

METHODS

Early menopause is associated with cardiovascular disease risk. We constructed a genetic risk score comprising 56 age-at-natural menopause decreasing alleles in men and women from the Framingham Heart Study, the Atherosclerosis Risk in Communities Study, and the Rotterdam Study. If the genetic predisposition to earlier age-at-natural menopause is associated with increased cardiovascular disease risk, it is reasonable to ask whether the risk is shared by men carrying the alleles, despite not experiencing menopause. We estimated the hazard ratio for the score for time to first cardiovascular event. To investigate the possible genetic pleiotropy between age-at-natural menopause and cardiovascular disease, we performed cross-trait linkage disequilibrium score regressions between age-at-natural menopause and cardiovascular disease and risk factors using genome-wide association studies.

RESULTS

Twenty-two thousand five hundred and sixty-eight cardiovascular disease-free participants at baseline were analyzed (9,808 men, 12,760 women). Each additional unit of the genetic propensity to earlier age-at-natural menopause increased the hazard of both cardiovascular disease and cardiac death in women (cardiovascular disease: hazard ratio 1.10 [1.04-1.16], P = 9.7 × 10; cardiac death: 1.12 [1.02-1.24], P = 0.03), whereas no effect was observed for either outcome in men (hazard ratio 0.99 [0.95-1.04], P = 0.71; 1.05 [0.94-1.16], P = 0.34). We found significant negative genetic correlations in women, but not men, between age-at-natural menopause and cardiovascular disease and risk factors.

CONCLUSION

Genetic variants associated with earlier age-at-natural menopause are associated with increased cardiovascular disease risk in women, but not men, suggesting sex-specific genetic effects on cardiovascular disease risk.

A polygenic risk score for breast cancer risk in a Taiwanese population

BACKGROUND

Multiple common variants identified by genome-wide association studies showed limited evidence of the risk of breast cancer in Taiwan. In this study, we analyzed the breast cancer risk in relation to 13 individual single-nucleotide polymorphisms (SNPs) identified by a GWAS in an Asian population.

METHODS

In total, 446 breast cancer patients and 514 healthy controls were recruited for this case-control study. In addition, we developed a polygenic risk score (PRS) including those variants significantly associated with breast cancer risk, and also evaluated the contribution of PRS and clinical risk factors to breast cancer using receiver operating characteristic curve (AUC).

RESULTS

Logistic regression results showed that nine individual SNPs were significantly associated with breast cancer risk after multiple testing. Among all SNPs, six variants, namely FGFR2 (rs2981582), HCN1 (rs981782), MAP3K1 (rs889312), TOX3 (rs3803662), ZNF365 (rs10822013), and RAD51B (rs3784099), were selected to create PRS model. A dose-response association was observed between breast cancer risk and the PRS. Women in the highest quartile of PRS had a significantly increased risk compared to women in the lowest quartile (odds ratio 2.26; 95% confidence interval 1.51-3.38). The AUC for a model which contained the PRS in addition to clinical risk factors was 66.52%, whereas that for a model which with established risk factors only was 63.38%.

CONCLUSIONS

Our data identified a genetic risk predictor of breast cancer in Taiwanese population and suggest that risk models including PRS and clinical risk factors are useful in discriminating women at high risk of breast cancer from those at low risk.

Interaction between common breast cancer susceptibility variants, genetic ancestry, and nongenetic risk factors in Hispanic women

BACKGROUND

Most genetic variants associated with breast cancer risk have been discovered in women of European ancestry, and only a few genome-wide association studies (GWAS) have been conducted in minority groups. This research disparity persists in post-GWAS gene-environment interaction analyses. We tested the interaction between hormonal and lifestyle risk factors for breast cancer, and ten GWAS-identified SNPs among 2,107 Hispanic women with breast cancer and 2,587 unaffected controls, to gain insight into a previously reported gene by ancestry interaction in this population.

METHODS

We estimated genetic ancestry with a set of 104 ancestry-informative markers selected to discriminate between Indigenous American and European ancestry. We used logistic regression models to evaluate main effects and interactions.

RESULTS

We found that the rs13387042-2q35(G/A) SNP was associated with breast cancer risk only among postmenopausal women who never used hormone therapy [per A allele OR: 0.94 (95% confidence intervals, 0.74-1.20), 1.20 (0.94-1.53), and 1.49 (1.28-1.75) for current, former, and never hormone therapy users, respectively, Pinteraction 0.002] and premenopausal women who breastfed >12 months [OR: 1.01 (0.72-1.42), 1.19 (0.98-1.45), and 1.69 (1.26-2.26) for never, <12 months, and >12 months breastfeeding, respectively, Pinteraction 0.014].

CONCLUSIONS

The correlation between genetic ancestry, hormone replacement therapy use, and breastfeeding behavior partially explained a previously reported interaction between a breast cancer risk variant and genetic ancestry in Hispanic women.

IMPACT

These results highlight the importance of understanding the interplay between genetic ancestry, genetics, and nongenetic risk factors and their contribution to breast cancer risk.

Association of three SNPs in TOX3 and breast cancer risk: Evidence from 97275 cases and 128686 controls

The associations of SNPs in TOX3 gene with breast cancer risk were investigated by some Genome-wide association studies and epidemiological studies, but the study results were contradictory. To derive a more precise estimate of the associations, we conducted a meta-analysis. ORs with 95% CI were used to assess the strength of association between TOX3 polymorphisms and breast cancer risk in fixed or random effect model. A total of 37 publications with 97275 cases and 128686 controls were identified. We observed that the rs3803662 C > T, rs12443621 A > G and rs8051542 C > T were all correlated with increased risk of breast cancer. In the stratified analyses by ethnicity, significantly elevated risk was detected for all genetic models of the three SNPs in Caucasians. In Asian populations, there were significant associations of rs3803662 and rs8051542 with breast cancer risk. Whereas there was no evidence for statistical significant association between the three SNPs and breast cancer risk in Africans. Additionally, we observed different associations of rs3803662 with breast cancer risk based on different ER subtype and BRCA1/BRCA2 mutation carriers. In conclusion, the meta-analysis suggested that three SNPs in TOX3 were significantly associated with breast cancer risk in different populations.

The use of the Gail model, body mass index and SNPs to predict breast cancer among women with abnormal (BI-RADS 4) mammograms

Introduction

Mammography screening results in a significant number of false-positives. The use of pretest breast cancer risk factors to guide follow-up of abnormal mammograms could improve the positive predictive value of screening. We evaluated the use of the Gail model, body mass index (BMI), and genetic markers to predict cancer diagnosis among women with abnormal mammograms. We also examined the extent to which pretest risk factors could reclassify women without cancer below the biopsy threshold.

Methods

We recruited a prospective cohort of women referred for biopsy with abnormal (BI-RADS 4) mammograms according to the American College of Radiology’s Breast Imaging-Reporting and Data System (BI-RADS). Breast cancer risk factors were assessed prior to biopsy. A validated panel of 12 single-nucleotide polymorphisms (SNPs) associated with breast cancer were measured. Logistic regression was used to assess the association of Gail risk factors, BMI and SNPs with cancer diagnosis (invasive or ductal carcinoma in situ). Model discrimination was assessed using the area under the receiver operating characteristic curve, and calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. The distribution of predicted probabilities of a cancer diagnosis were compared for women with or without breast cancer.

Results

In the multivariate model, age (odds ratio (OR) = 1.05; 95% confidence interval (CI), 1.03 to 1.08; P < 0.001), SNP panel relative risk (OR = 2.30; 95% CI, 1.06 to 4.99, P = 0.035) and BMI (≥30 kg/m² versus <25 kg/m²; OR = 2.20; 95% CI, 1.05 to 4.58; P = 0.036) were significantly associated with breast cancer diagnosis. Older women were more likely than younger women to be diagnosed with breast cancer. The SNP panel relative risk remained strongly associated with breast cancer diagnosis after multivariable adjustment. Higher BMI was also strongly associated with increased odds of a breast cancer diagnosis. Obese women (OR = 2.20; 95% CI, 1.05 to 4.58; P = 0.036) had more than twice the odds of cancer diagnosis compared to women with a BMI <25 kg/m². The SNP panel appeared to have predictive ability among both white and black women.

Conclusions

Breast cancer risk factors, including BMI and genetic markers, are predictive of cancer diagnosis among women with BI-RADS 4 mammograms. Using pretest risk factors to guide follow-up of abnormal mammograms could reduce the burden of false-positive mammograms.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-014-0509-4) contains supplementary material, which is available to authorized users.

The relationship between RAGE gene four common polymorphisms and breast cancer risk in northeastern Han Chinese

We aimed to evaluate the association of four common polymorphisms (rs1800625, rs1800624, rs2070600, and rs184003) in receptor for advanced glycation end products (RAGE) gene to evaluate their epistatic influence on breast cancer risk in northeastern Han Chinese. This is a hospital-based case-control study involving 509 histologically-proven breast cancer patients and 504 cancer-free controls. The genotype and allele distributions of rs184003 differed significantly between patients and controls, even after the Bonferroni correction. Individuals carrying the rs184003 T allele exhibited 1.62-fold increased risk of breast cancer (odds ratio (OR) = 1.62; 95% confidence interval (95% CI): 1.26–2.08; P < 0.001) after adjusting for confounders. The frequency of haplotype T-T-G-T (alleles in order of rs1800625, rs1800624, rs2070600, and rs184003) was remarkably higher in patients than in controls (Simulated P = 0.001), and this haplotype was significantly associated with a 1.43-fold (95% CI: 1.01–2.01; P = 0.041) increase in adjusted risk of breast cancer. Further analysis indicated that there was synergistic interaction between rs184003 and rs2070600, whereas their joint information gain value was relatively small (0.27%). Taken together, although there was no suggestive evidence for the presence of epistasis in RAGE gene, our findings clearly demonstrate that rs184003 might play a predominant role in the development of breast cancer.