Grant Number:	1R01CA317515-01 Interpret this number
Primary Investigator:	Sieh, Weiva
Organization:	University Of Tx Md Anderson Can Ctr
Project Title:	Multi-Ancestry Study of Mammographic Density
Fiscal Year:	2026

ABSTRACT High mammographic density (MD) is a strong and common risk factor for breast cancer that accounts for a greater proportion of breast cancers in U.S. women than any other risk factor. In addition, high MD decreases the sensitivity of screening mammography, and the FDA now mandates informing all women if they have dense breasts. MD phenotypes are highly heritable, but the genetic bases of MD and its association with breast cancer risk remain largely unknown. Prior genome-wide (GWAS) and transcriptome-wide (TWAS) association studies of MD in women of mostly European ancestry explain only a small fraction of the heritability. Moreover, the distribution of MD varies significantly by race/ethnicity after adjusting for other risk factors, but the causes of this variation are poorly understood. Importantly, MD phenotypes can be modified by nongenetic factors such as hormonal therapy and alcohol use. Yet, few prior studies have examined associations of nongenetic factors with quantitative MD phenotypes, and their potential to modify genetic risk factors, in large multiethnic populations. Here, we propose to conduct the first large multi-ancestry study of both the genetic and nongenetic determinants of quantitative MD phenotypes in >120K multiethnic women. The inclusion of multiple ancestries not only improves gene discovery for complex traits, but also is essential for improving health in all populations. The specific aims are: Aim 1 Conduct multi-ancestry GWAS of MD phenotypes, accounting for both global and local ancestry, to improve the power to detect ancestry-specific and shared loci. We will determine whether novel MD loci also are associated with breast cancer risk in a multiethnic population of >350K cases and >250K controls from the NCI Confluence study to identify the most promising targets for prevention strategies. Aim 2 Identify genes associated with MD phenotypes through multiple levels of gene regulation using ancestry-aware transcriptomic analysis. We will develop new ancestry-specific prediction models for multiple regulatory layers (gene and isoform expression, splicing events) in normal breast tissue to substantially boost the power of gene discovery. We will conduct the first multi-ancestry, multi-level TWAS of MD phenotypes, and determine whether newly discovered MD genes also are associated with breast cancer risk. Aim 3 Assess associations of nongenetic risk factors with quantitative MD phenotypes in a large multiethnic population, and explore whether genetic effects are modified by other factors. The proposed research is significant and innovative because it will be the first large multi-ancestry study of the genetic and nongenetic determinants of quantitative MD phenotypes, and will generate new multi-ancestry normal breast transcriptomic reference panels and statistical methodology that will be shared publicly. The results will improve our understanding of the biological bases of MD and its association with breast cancer risk, provide new insights into the sources of variation across racial/ethnic groups, and help guide prevention strategies to improve breast health in all U.S. women.





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