Genetic variation in peroxisome proliferator-activated receptor gamma, soy, and mammographic density in Singapore Chinese women

Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review

BACKGROUND

Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density.

METHODS

The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed.

RESULTS

Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait.

CONCLUSION

Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.

Understanding mammographic breast density profile in China: A Sino-Australian comparative study of breast density using real-world data from cancer screening programs

AIM

This study aims at understanding mammographic density profile in China by comparing the density between women in China and Australia.

METHODS

Data of 3250 women aged 45-69 were obtained from the Cancer Screening Program in Urban China and data of 1384 Australian counterparts at same age range were gathered from the Lifepool project. Demographic and reproductive details and mammograms for each cohort were collected. Mammographic density was assessed using AutoDensity, and two metrics, percentage density (PD) and dense area (DA), were applied. T-tests were used to compare the means of mammographic density between two populations of all, premenopausal, and postmenopausal women. Two-way ANOVA was conducted to examine interactions of population (Chinese/Australian) and each variable of interest upon mammographic density.

RESULTS

Chinese women had 9.61%, 8.20%, and 9.28% higher PD than their Australian counterparts in all, premenopausal, and postmenopausal women, respectively (all p < 0.001). The mean differences in DA between two population were 1.81 cm² (p < 0.001), 0.55 cm² (p = 0.472), and 1.76 cm² (p = 0.003) for all, premenopausal, and postmenopausal women, respectively. There were significant interactions between population and age (F[4, 4624] = 4.12, p = 0.003), BMI (F[2, 4628] = 3.92, p = 0.020), age at first birth (F[1, 4250] = 11.69, p < 0.001), breastfeeding history (F[1, 4479] = 17.79, p < 0.001), and breastfeeding duration (F[1, 3526] = 66.90, p < 0.001) upon PD. Interaction was only found for breastfeeding history (F[1, 4479] = 4.79, p = 0.029) and breastfeeding duration (F[1, 3526] = 17.72, p < 0.001) for DA.

CONCLUSIONS

Both PD and DA were found to be higher in Chinese women compared to Australian women. The density difference by menopause status was shown and breastfeeding history affected breast density differently in both populations.

PPARGC1A gene polymorphism is associated with exercise-induced fat loss

Obesity is a widespread problem within modern society, serving to increase the risk of cardiovascular, metabolic, and neurodegenerative disorders. Peroxisome proliferator-activated receptor gamma (PPARγ) and PPARγ coactivator 1 α (PGC1α) play a key role in the regulation of cellular energy metabolism and is implicated in the pathology of these diseases. This study examined the association between polymorphisms of the PPARG and PPARGC1A genes and individual variability in weight loss in response to physical activity intervention. 39 obese Ukrainian women (44.4 ± 7.5 years, BMI > 30.0 kg/m²) undertook a 3-month fitness program whilst following a hypocaloric diet (~ 1500 cal). Anthropometric and biochemical measurements took place before and after the program. Single nucleotide polymorphisms within or near PPARG (n = 94) and PPARGC1A (n = 138) were identified and expression of PPARG mRNA was measured via reverse transcription and amplification. The association between DNA polymorphisms and exercise-induced weight loss, initial body mass, biochemistry and PPARG expression was determined using one-way analysis of variance (ANOVA). The present intervention induced significant fat loss in all participants (total fat: 40.3 ± 5.3 vs 36.4 ± 5.7%; P < 0.00001). Only one polymorphism (rs17650401 C/T) within the PPARGC1A gene was found to be associated with fat loss efficiency after correction for multiple testing, with T allele carriers showing the greatest reduction in body fat percentage (2.5-fold; P = 0.00013) compared to non-carriers. PPARGC1A (rs17650401) is associated with fat loss efficiency of the fitness program in obese women. Further studies are warranted to test whether this variation is associated with fat oxidation.

Breast cancer risk factors and mammographic density among high-risk women in urban China

Elevated mammographic density (MD) is an established breast cancer risk factor. Studies examining relationships between MD and breast cancer risk factors are limited in China, where established breast cancer risk factors are less prevalent but dense breasts are more prevalent than Western countries. This study included 11,478 women (45-69 years; 36% premenopausal) participating in an ongoing national cancer screening program in 11 urban provinces in China and predicted as having high-risk for breast cancer. Polytomous logistic regression was performed to assess associations between MD and risk factors by comparing each higher Breast Imaging Reporting and Data System (BI-RADS) category (2, 3, or 4) to the lowest category (BI-RADS, 1). We found associations of increasing age, body mass index, weight, postmenopausal status, and parity with lower MD. Higher levels of education, increasing height, and later first birth were associated with higher MD. These associations did not vary by menopausal status. Additionally, the association between longer period of breastfeeding and lower MD was seen among postmenopausal women only (P_interaction = 0.003). Having first-degree relatives with breast cancer diagnosed before 50 years was associated with lower MD only among premenopausal women (P_interaction = 0.061). We found effects of established breast cancer risk factors on MD showed similar directions in Chinese and Western women, supporting the hypothesis that MD represents cumulative exposure to breast cancer risk factors over the life course. Our findings help to understand the biological basis of the association of MD with breast cancer risk and have implications for breast cancer prevention research in China.

A Randomized Controlled Trial of Green Tea Extract Supplementation and Mammographic Density in Postmenopausal Women at Increased Risk of Breast Cancer

Epidemiologic and animal studies suggest a protective role of green tea against breast cancer. However, the underlying mechanism is not understood. We conducted a randomized, double-blinded, placebo-controlled phase II clinical trial to investigate whether supplementation with green tea extract (GTE) modifies mammographic density (MD), as a potential mechanism, involving 1,075 healthy postmenopausal women. Women assigned to the treatment arm consumed daily 4 decaffeinated GTE capsules containing 1,315 mg total catechins, including 843 mg epigallocatechin-3-gallate (EGCG) for 12 months. A computer-assisted method (Madena) was used to assess MD in digital mammograms at baseline and month 12 time points in 932 completers (462 in GTE and 470 in placebo). GTE supplementation for 12 months did not significantly change percent MD (PMD) or absolute MD in all women. In younger women (50-55 years), GTE supplementation significantly reduced PMD by 4.40% as compared with the placebo with a 1.02% PMD increase from pre- to postintervention (P = 0.05), but had no effect in older women (Pinteraction = 0.07). GTE supplementation did not induce MD change in other subgroups of women stratified by catechol-O-methyltransferase genotype or level of body mass index. In conclusion, 1-year supplementation with a high dose of EGCG did not have a significant effect on MD measures in all women, but reduced PMD in younger women, an age-dependent effect similar to those of tamoxifen. Further investigation of the potential chemopreventive effect of green tea intake on breast cancer risk in younger women is warranted. Cancer Prev Res; 10(12); 710-8. ©2017 AACR.

Biological underpinnings of breastfeeding challenges: the role of genetics, diet, and environment on lactation physiology

Lactation is a dynamic process that has evolved to produce a complex biological fluid that provides nutritive and nonnutritive factors to the nursing offspring. It has long been assumed that once lactation is successfully initiated, the primary factor regulating milk production is infant demand. Thus, most interventions have focused on improving breastfeeding education and early lactation support. However, in addition to infant demand, increasing evidence from studies conducted in experimental animal models, production animals, and breastfeeding women suggests that a diverse array of maternal factors may also affect milk production and composition. In this review, we provide an overview of our current understanding of the role of maternal genetics and modifiable factors, such as diet and environmental exposures, on reproductive endocrinology, lactation physiology, and the ability to successfully produce milk. To identify factors that may affect lactation in women, we highlight some information gleaned from studies in experimental animal models and production animals. Finally, we highlight the gaps in current knowledge and provide commentary on future research opportunities aimed at improving lactation outcomes in breastfeeding women to improve the health of mothers and their infants.

Variants in 6q25.1 Are Associated with Mammographic Density in Malaysian Chinese Women

BACKGROUND

Mammographic density is an established risk factor for breast cancer and has a strong heritable component. Genome-wide association studies (GWAS) for mammographic density conducted in women of European descent have identified several genetic associations, but none of the studies have been tested in Asians. We sought to investigate whether these genetic loci, and loci associated with breast cancer risk and breast size, are associated with mammographic density in an Asian cohort.

METHODS

We conducted genotyping by mass spectrometry in 1,189 women (865 Chinese, 187 Indian, and 137 Malay). Quantitative measurements of mammographic density were performed using ImageJ, a fully automated thresholding technique. The associations of SNPs to densities were analyzed using linear regression models.

RESULTS

We successfully evaluated the associations of 36 SNPs with mammographic densities. After adjusting for age, body mass index, parity, and menopausal status, we found that in our cohort of 865 Malaysian Chinese, three SNPs in the 6q25.1 region near ESR1 (rs2046210, rs12173570, and rs10484919) that were associated with mammographic density, breast cancer risk, or breast size in previous GWAS were significantly associated with both percentage density and absolute dense area. We could not replicate the most significant association found previously in European women (rs10995190, ZNF365 gene) because the minor allele was absent for Asian women.

CONCLUSION

We found that the directions of genetic associations were similar to those reported in Caucasian women.

IMPACT

Our results show that even in Asian women with lower population risk to breast cancer, there is shared heritability between mammographic density and breast cancer risk.

Peroxisome proliferator-activated receptor γ2 Pro12Ala (rs1801282) polymorphism and breast cancer susceptibility: a meta-analysis

Several studies have investigated the correlation between the peroxisome proliferator-activated receptor γ2 (PPAR‑γ2) Pro12Ala (rs1801282) polymorphism and the risk of breast cancer, with inconsistent results. For this reason, a meta-analysis was conducted to identify the potential correlation after pooling data from eligible case-control studies. Search strategies were conducted in PubMed, EMBASE and the COCHRANE Library in English and from VIP, CNKI and Sinomed in Chinese (all the papers were published before November 11, 2012) using appropriate terms. A total of 2,279 cases and 2,360 controls from four related case-control studies were included in this meta-analysis. According to the three eligible populations, the odds ratios (ORs) and 95% confidence intervals (CIs) on the risk of breast cancer for the CG versus CC and GG versus CC genotypes and the G versus C allele were 0.84 and 0.72-0.98, 0.92 and 0.32-2.61, and 0.98 and 0.84-1.13, respectively. The OR and 95% CI for CG+GG versus CC from the four study populations were 0.85 and 0.73-0.98, respectively. This meta-analysis supported the fact that the G allele of PPAR‑γ2 Pro12Ala (rs1801282) modestly affects the risk of breast cancer. Nevertheless, further studies are required to enrich the evidence of this correlation.

Variation in inflammatory cytokine/growth-factor genes and mammographic density in premenopausal women aged 50-55

Background

Mammographic density (MD) has been found to be an independent risk factor for breast cancer. Although data from twin studies suggest that MD has a strong genetic component, the exact genes involved remain to be identified. Alterations in stromal composition and the number of epithelial cells are the most predominant histopathological determinants of mammographic density. Interactions between the breast stroma and epithelium are critically important in the maturation and development of the mammary gland and the cross-talk between these cells are mediated by paracrine growth factors and cytokines. The potential impact of genetic variation in growth factors and cytokines on MD is largely unknown.

Methods

We investigated the association between 89 single nucleotide polymorphisms (SNPs) in 7 cytokine/growth-factor genes (FGFR2, IGFBP1, IGFBP3, TGFB1, TNF, VEGF, IL6) and percent MD in 301 premenopausal women (aged 50 to 55 years) participating in the Norwegian Breast Cancer Screening Program. We evaluated the suggestive associations in 216 premenopausal Singapore Chinese Women of the same age.

Results

We found statistically significant associations between 9 tagging SNPs in the IL6 gene and MD in Norwegian women; the effect ranged from 3–5% in MD per variant allele (p-values = 0.02 to 0.0002). One SNP in the IL6 (rs10242595) significantly influenced MD in Singapore Chinese women.

Conclusion

Genetic variations in IL6 may be associated with MD and therefore may be an indicator of breast cancer risk in premenopausal women.

Hormone metabolism genes and mammographic density in Singapore Chinese women

BACKGROUND

Female steroid hormone levels and exogenous hormone use influence breast cancer risk. We investigated the association between genetic variation in the hormone metabolism and signaling pathway and mammographic density, a strong predictor of breast cancer risk.

METHODS

We genotyped 161 SNPs in 15 hormone metabolism pathway gene regions and evaluated mammographic density in 2,038 Singapore Chinese women. Linear regression analysis was used to investigate single-nucleotide polymorphism (SNP) and mammographic density association. An overall pathway summary was obtained using the adaptive ranked truncated product test.

RESULTS

We did not find any of the individually tested SNPs to be associated with mammographic density after a multiple testing correction. There was no evidence of an overall effect on mammographic density of genetic variation in the hormone metabolism pathway.

CONCLUSIONS

In this cross-sectional study, genetic variation in hormone metabolism pathway was not associated with mammographic density in Singapore Chinese women.

IMPACT

Consistent with existing data from Caucasian populations, polymorphisms in hormone pathway genes are not likely to be strong predictors of mammographic density in Asian women.

Genetic variation in transforming growth factor beta 1 and mammographic density in Singapore Chinese women

TGF-β plays a critical role in normal mammary development and morphogenesis. Decreased TGF-β signaling has been associated with increased mammographic density. Percent mammographic density (PMD) adjusted for age and body mass index (BMI) is a strong risk factor and predictor of breast cancer risk. PMD is highly heritable, but few genetic determinants have been identified. We investigated the association between genetic variation in TGFB1 and PMD using a cross-sectional study of 2,038 women who were members of the population-based Singapore Chinese Health Study cohort. We assessed PMD using a computer-assisted method. We used linear regression to examine the association between nine tagging single-nucleotide polymorphisms (SNP) of TGFB1 and PMD and their interaction with parity, adjusting for age, BMI, and dialect group. We calculated P values adjusted for correlated tests (P(ACT)) to account for multiple testing. The strongest association was observed for rs2241716. Adjusted PMD was higher by 1.5% per minor allele (P(ACT) = 0.04). When stratifying by parity, this association was limited to nulliparous women. For nulliparous women, adjusted PMD was higher by 8.6% per minor allele (P(ACT) = 0.003; P for interaction with parity = 0.002). Three additional TGFB1 tagging SNPs, which were in linkage disequilibrium with rs2241716, were statistically significantly associated with adjusted PMD (P(ACT) < 0.05) for nulliparous women. However, none of these three SNPs showed statistically significant association after adjusting for rs2241716. Our data support that TGFB1 genetic variation may be an important genetic determinant of mammographic density measure that predicts breast cancer risk, particularly in nulliparous women.