Breast cancer remains the most frequent malignant tumor that occurs in the glandular epithelium of breast (1), and accounts for approximately 12% of the total 9.6 million deaths due to cancer (2). Since 1970s, the incidence rate of breast cancer worldwide has continued to increase; it is reported that one in eight women suffered from this type of cancer in USA (3). Although mammary gland is not an important organ to maintain human life and breast cancer in situ is not fatal, breast cancer cells may lose characteristics of normal cells and is easy to fall off due to the loose connection among cells. Once falling off, cancer cells would spread throughout the body with blood or lymph, leading to cancer metastasis and thus endangering life (4). Over the past few decades the treatment of breast cancer has been advanced greatly, but the overall survival is still not optimistic (1, 5). Therefore, it is particularly important to understand the etiology, occurrence, and development of breast cancer for early prevention. Existing studies have identified a series of risk factors involved in breast cancer, including dietary habit, age at first birth, age at menarche, age at menopause, family history, excessive intake of exogenous hormones as well as genetic mutations such as BRCA1, BRCA2, and PIK3CA (1, 6–10).
However, these traditionally established risk factors during women’s adult life appear not to adequately interpretate the occurrence pattern of breast cancer. To advance our understanding of disease causes, the relationship between breast cancer and early growth/development, perinatal intrauterine environments has been attracted much attention since 1990s (11–23). Among those, the association between birthweight and breast cancer has been attracted much research interest. Although a positive correlation between women’s birthweight and breast cancer risk was discovered in some studies (11, 12, 20, 23–32), some others failed to replicate such connection or even detected inconsistent correlations in effect direction (13, 15, 21, 22, 33–41). These inconsistent findings may be partly due to potential confounding influences commonly arisen in observational studies, making it difficult to draw a definitive conclusion on the causal association between birthweight and breast cancer. In addition, it is not clear whether there exists a mediating association between the two traits (20, 42).
Furthermore, from a genetic perspective, it is also not known whether the observed co-existence of low/high birthweight and breast cancer is partly driven by causal association or shared genetic background between the two traits. All prior studies cannot distinguish the maternal-specific and fetal-specific effects of birthweight on breast cancer from each other. Compared to other factors, birthweight is a special exposure proxy genetically affected by both mother’s and offspring’s genotypes (43). Therefore, partitioning the overall effect of birthweight into maternal-specific and fetal-specific components holds the key for understanding the origin of the association between birthweight and breast cancer. Although the longitudinal cohort study can provide empirical evidence for causal inference, it requires large-scale populations and long-term follow-up before the onset of breast cancer (44); consequently, the implementation is not easy. In the traditional scenario, randomized controlled trial is the gold standard for inferring causality, but such study is also infeasible to investigate the causal association between birthweight and breast cancer (29). In addition, both the two types of studies cannot resolve the maternal-specific and fetal-specific impacts of birthweight on adult diseases including breast cancer.
The present work attempted to answer these critical questions via genetic analysis using summary-level data available from large-scale genome-wide association studies (GWASs). First, to assess the extent of genetic overlap shared between birthweight and breast cancer, we applied the cross-trait linkage disequilibrium score regression (LDSC) to quantify the genetic correlation between them (45). Second, we employed a novel pleiotropy test method called MAIUP (Mixture Adjusted Intersect-Union Pleiotropy test) to determine pleiotropic genes (46–48). Third, to elaborate the causal association between birthweight and breast cancer, we resorted to apply Mendelian randomization (MR) methods (49–52). In the MR analysis, genetic variants, which are required to be associated with the exposure of focus, are used as instrumental variables, based on which the causal association between the exposure (e.g., birthweight) and the disease (e.g., breast cancer) can be inferred. Recently, one MR study was performed but found no evidence supporting the causal association between birthweight and breast cancer (53). However, that study did not explore the separate maternal-specific and fetal-specific effects of birthweight on breast cancer. The summary statistics of maternal/fetal-specific effects of SNPs (single nucleotide polymorphisms) on birthweight, released by a recent GWAS (43), offers us an unprecedented opportunity to untangle the maternal and fetal contributions of birthweight to breast cancer by using novel MR methods. Furthermore, as a byproduct of our MR analysis, we can evaluate the mediating relationship between birthweight and breast cancer, with age of menarche and age at menopause as two candidate mediators. The flow diagram of data process and statistical analysis for the present study is illustrated in Figure 1.