No evidence for association of inherited variation in genes involved in mitosis and percent mammographic density

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.

Breast Cancer Screening Strategies for Women With ATM, CHEK2, and PALB2 Pathogenic Variants: A Comparative Modeling Analysis

IMPORTANCE

Screening mammography and magnetic resonance imaging (MRI) are recommended for women with ATM, CHEK2, and PALB2 pathogenic variants. However, there are few data to guide screening regimens for these women.

OBJECTIVE

To estimate the benefits and harms of breast cancer screening strategies using mammography and MRI at various start ages for women with ATM, CHEK2, and PALB2 pathogenic variants.

DESIGN, SETTING, AND PARTICIPANTS

This comparative modeling analysis used 2 established breast cancer microsimulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate different screening strategies. Age-specific breast cancer risks were estimated using aggregated data from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium for 32 247 cases and 32 544 controls in 12 population-based studies. Data on screening performance for mammography and MRI were estimated from published literature. The models simulated US women with ATM, CHEK2, or PALB2 pathogenic variants born in 1985.

INTERVENTIONS

Screening strategies with combinations of annual mammography alone and with MRI starting at age 25, 30, 35, or 40 years until age 74 years.

MAIN OUTCOMES AND MEASURES

Estimated lifetime breast cancer mortality reduction, life-years gained, breast cancer deaths averted, total screening examinations, false-positive screenings, and benign biopsies per 1000 women screened. Results are reported as model mean values and ranges.

RESULTS

The mean model-estimated lifetime breast cancer risk was 20.9% (18.1%-23.7%) for women with ATM pathogenic variants, 27.6% (23.4%-31.7%) for women with CHEK2 pathogenic variants, and 39.5% (35.6%-43.3%) for women with PALB2 pathogenic variants. Across pathogenic variants, annual mammography alone from 40 to 74 years was estimated to reduce breast cancer mortality by 36.4% (34.6%-38.2%) to 38.5% (37.8%-39.2%) compared with no screening. Screening with annual MRI starting at 35 years followed by annual mammography and MRI at 40 years was estimated to reduce breast cancer mortality by 54.4% (54.2%-54.7%) to 57.6% (57.2%-58.0%), with 4661 (4635-4688) to 5001 (4979-5023) false-positive screenings and 1280 (1272-1287) to 1368 (1362-1374) benign biopsies per 1000 women. Annual MRI starting at 30 years followed by mammography and MRI at 40 years was estimated to reduce mortality by 55.4% (55.3%-55.4%) to 59.5% (58.5%-60.4%), with 5075 (5057-5093) to 5415 (5393-5437) false-positive screenings and 1439 (1429-1449) to 1528 (1517-1538) benign biopsies per 1000 women. When starting MRI at 30 years, initiating annual mammography starting at 30 vs 40 years did not meaningfully reduce mean mortality rates (0.1% [0.1%-0.2%] to 0.3% [0.2%-0.3%]) but was estimated to add 649 (602-695) to 650 (603-696) false-positive screenings and 58 (41-76) to 59 (41-76) benign biopsies per 1000 women.

CONCLUSIONS AND RELEVANCE

This analysis suggests that annual MRI screening starting at 30 to 35 years followed by annual MRI and mammography at 40 years may reduce breast cancer mortality by more than 50% for women with ATM, CHEK2, and PALB2 pathogenic variants. In the setting of MRI screening, mammography prior to 40 years may offer little additional benefit.

Single nucleotide polymorphisms in the non-coding region of STIM1 gene are associated with Parkinson disease risk in Chinese Han population

The stromal interaction molecule 1 (STIM1) gene contributes essentially to Ca transport, thus it is functionally related to neurodegenerative disorders. The objective of this study was to investigate the correlation between single nucleotide polymorphisms (SNP) in the non-coding region of STIM1 gene and the risk for Parkinson disease (PD) in a Chinese Han population.In a cohort composed of 300 PD patients and 300 healthy individuals from a Chinese Han population, we analyzed genotypes for five novel SNPs, rs7934581, rs3794050, rs1561876, rs3750994 and rs3750996 in the non-coding region of STIM1 gene. The levels of STIM1 protein in plasma of these subjects were also assessed by enzyme-linked immunosorbent assay (ELISA).We found that the SNPs of STIM1 gene rs7934581, rs3794050, rs1561876, and rs3750996 were associated with increased PD risk, while rs3750994 SNP was not. An increased risk of PD was observed in subjects with the TAAG and TGAG haplotypes of rs7934581, rs3794050, rs1561876, rs3750996. Moreover, PD risk was significantly elevated only in subjects with age ≥60 years or females who carry the STIM1 rs3794050 minor allele. There was a significant difference in plasma STIM1 protein levels between subjects with different genotypes of STIM1 rs7934581, rs3794050, rs1561876, and rs3750996.STIM1 gene rs7934581, rs3794050, rs1561876, rs3750996 SNPs are associated with increased PD risk, and its mechanism may be related to abnormal STIM1 gene expression.