Investigating the interaction between genetic breast cancer risk and epigenome

Research into genetic risk factors for breast cancer has yielded polygenic risk scores (PRSs). However, genetic risk factors such as polygenic risk scores are static. To follow a person’s changing environment and health, dynamic markers are required. In a new manuscript published in npj Precision Oncology, we investigated the interaction between the epigenome and genetic background at methylation quantitative trait loci (mQTLs) associated with breast cancer.

Our results indicate that although methylation levels at methylation QTLs are genetically determined, they show variability across cell types. This variability may carry information about non-heritable changes in risk. For breast cancer, cervical samples with a high epithelial cell content carried the largest amount of variability.

Variability across mQTL sites or all CpGs in cervical, buccal, or blood samples of varying immune cell proportion.

A linear combination of methylation values at 104 mQTL sites, termed the ‘Women’s cancer risk identification - quantitative trait index for breast cancer’, or simply WID™-qtBC, detects current cancer cases with an AUC of 0.71 in cervical samples.

The methylation-based WID™-qtBC was modified by age and other nonheritable factors associated with breast cancer risk, including body mass index or age at menopause. Interestingly, the correlation between the polygenic risk score (PRS) and mQTL index was weak. However, women with both a high PRS and high WID-qtBC score exhibited a 9.6-fold increased risk for being diagnosed with breast cancer, indicating an interaction of genetic and non-genetic risk factors at the level of the epigenome.

The WID™-qtBC detects current breast cancer cases with an area under the curve of 0.71 in an external validation set. The WID™-qtBC is increased with chronological age, a key risk factor for breast cancer.

Our data suggest that the WID™-qtBC alone or in combination with the PRS may improve breast cancer risk stratification compared to current methods, but further research is required to validate our findings.

Read the article:

2023

DNA methylation at quantitative trait loci (mQTLs) varies with cell type and nonheritable factors and may improve breast cancer risk assessment

Chiara Herzog, Allison Jones, Iona Evans, and 8 more authors

npj Precision Oncology, 2023

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To individualise breast cancer (BC) prevention, markers to follow a person’s changing environment and health extending beyond static genetic risk scores are required. Here, we analysed cervical and breast DNA methylation (n=1848) and single nucleotide polymorphisms (n=1442) and demonstrate that a linear combination of methylation levels at 104 BC-associated methylation quantitative trait loci (mQTL) CpGs, termed the WID™-qtBC index, can identify women with breast cancer in hormone-sensitive tissues (AUC=0.71 [95% CI: 0.65–0.77] in cervical samples). Women in the highest combined risk group (high polygenic risk score and WID™-qtBC) had a 9.6-fold increased risk for BC [95% CI: 4.7–21] compared to the low-risk group and tended to present at more advanced stages. Importantly, the WID™-qtBC is influenced by non-genetic BC risk factors, including age and body mass index, and can be modified by a preventive pharmacological intervention, indicating an interaction between genome and environment recorded at the level of the epigenome. Our findings indicate that methylation levels at mQTLs in relevant surrogate tissues could enable integration of heritable and non-heritable factors for improved disease risk stratification.

2023

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