New Methods for Genomic Studies in African American Women

Institution: University of Southern California
Investigator(s): Daniel  Stram , Ph.D. -
Award Cycle: 2009 (Cycle 15) Grant #: 15UB-8402 Award: $411,297
Award Type: SRI Request for Proposal (RFP)
Research Priorities
Etiology and Prevention>Prevention and Risk Reduction: ending the danger of breast cancer

Initial Award Abstract (2009)

Introduction: Genome-wide association scan (GWAS) studies identify which genes are associated with disease by looking at hundreds of thousands genetic markers (polymorphisms) in large numbers of people with and without disease. GWAS studies of breast cancer have already yielded important information regarding a woman’s inherited risk of breast cancer; however, much about disease susceptibility and about ethnic or racial disparities in the burden of disease is still to be learned. Now for the first time a GWAS study is producing data for African American women with breast cancer: the African American Breast Cancer (AABC) study. This US-wide consortium of studies of African American breast cancer cases and controls represents a large investment of money and other resources. Over 1 million genetic markers are being analyzed for these study participants in order to find genes associated with increased risk of breast cancer in African American women.

Detailed studies of the genetics of breast cancer among African American women are necessary as a part of the effort to fully understand breast cancer pathways and biology as well as to understand racial/ethnic disparities in this disease. Further development of statistical methods to address the complex data coming from the AABC study is necessary to obtain maximum scientific value from the important investment that this study represents.

Hypotheses: New statistical methods and techniques can be applied to the AABC data to better understand the relationship between disease risk and over 1 million measurements of genetic variation for each study participant.

General methodology: We will develop statistical methods, and apply them along with other new and established methods to analyze the AABC study data. We will conduct computer-based realistic simulation studies (based on evolutionary simulation techniques) to determine which of the statistical techniques can be expected to give the best results with real data. The analysis of the AABC data will also attempt to find new disease associations that help understand differences in individual, genetic susceptibility to breast cancer.

Innovative elements: GWAS studies have engendered much novel statistical research into how best to analyze the resulting data to detect disease associations. We will develop and evaluate novel methods and compare these to other methods, including some that are newly proposed but not yet fully explored.

Final Report (2014)

Brief Overview: This project was based around the first genome-wide look at genetic variants related to breast cancer in a large sample of African American women (called the AABC study) half with breast cancer (cases) and half without (controls). The CBCRP funded project focused on statistical methodology problems related to the analysis of these data and to the use of these data in conjunction with other diseases or outcomes. These aims included: development and application of haplotype-based methods for testing disease associations (a special kind of statistical analysis of the relationship between genetic variants and breast cancer risk); design of DNA sequencing studies for follow-up of initial associations in order to more identify the most likely genetic cause underlying the haplotype-based associations, see below; and novel work on fully utilizing the contributions of people of historically mixed populations, such as African American women, to disease association studies.

Degree to which project aims were accomplished: Several of the project goals were fully accomplished. For example we published a paper in the journal PLOS Genetics (Chen et al 2010) on assessing the long-term value of the AABC genome-wide genetic data not only for future studies of breast cancer, but also in studies of other diseases of importance in African Americans; the results of this work is now being utilized in a NIH funded study of the genetics of multiple myeloma in African Americans (who have a high rate of this type of cancer, compared to other U.S. ethnic groups). In the multiple myeloma (MM) study only cases (people with MM) are being entered in the study, the AABC data is providing the necessary controls thereby simplifying the MM study and enhancing the value of the AABC data. With regard to the same general topic we also have just submitted a paper (Zhang and Stram, see list below) for journal review on the role of local ancestry adjustment (which takes account of the ancestry of each chromosomal region for people of mixed origin) in association studies. It should be noted that most genetic studies to date have focused mainly on people of European ancestry with many fewer studies involving large numbers of African Americans or other mixed groups such as the U.S. Latino populations.

We also published the results, in the journal PLOS ONE) of a haplotype-based search for additional breast cancer associations (Song et al, 2013). Haplotype analysis is a form of genetic analysis needed to most fully utilize the AABC study data to investigate the genetic risk of breast cancer in African American women. The Song et al paper both solves certain statistical problems related to haplotype analysis, and presented results of a genome-wide search. This paper finds several new genetic locations which may contain risk-related genetic variants. These analyses will need to be followed up in additional studies.

The work on design of sequencing studies is still ongoing. Genetic sequencing is a much more expensive, but more complete, method of measuring genetic differences between individuals or groups of people (such as cases and controls with or without breast cancer). We have contributed some of the AABC data (with the permission of all investigators) to another grant, which is looking more closely at design of sequencing studies then we were able to on our own at this time. Barriers that were overcome or not overcome: The primary problem (both for this grant, and the grants that funded the AABC study) that has yet to be fully overcome is that very, very large studies turn out to be necessary to really assess fully genetic contributions to complex diseases such as breast cancer. These extremely large studies require additional resources which can only come with a national effort. Outside of this grant investigators at U.S.C. are making important strides in developing these large datasets, and the AABC study is an important contributor, but much further work needs to be performed.

List of major accomplishments: Our major accomplishment was to write eight papers (seven published one in review) on the general topic of analysis of genetic causes of breast cancer in African American women and/or related analysis issues. Not all of these papers were solely funded by the CBCRP but all cite the CBCRP grant for either full or partial support of one or more investigators. In particular, Chen F (lead author for 3 papers), and Song C (lead author for 1 paper), were both fully funded by the CBCRP grant for one or more years. Daniel Stram was partially funded for all years of the project (senior author on 4 papers).

Plans for continuation of this research topic: The general topic of genetic analysis of African American breast cancer risk and risk of other cancers and outcomes in historically mixed groups is now a major research topic at U.S.C. Keck School of Medicine, and also at a number of other institutions that we collaborate closely with. Both methodological and applied problems are being dealt with by a wide group of investigators especially those (such as Daniel Stram, Haiman, and Loic Le Marchand) who are associated with the Multiethnic Cohort Study in Hawaii and Los Angeles. The CBCRP grant (by funding investigators and students) has been vital in kick-starting statistical methods at U.S.C. on the statistical problems related to this important effort.

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data
Caution in generalizing known genetic risk markers for breast cancer across all ethnic/racial populations. Eur J Hum Genet 19: 243–245.
The potential for enhancing the power of genetic association studies in African Americans through the reuse of existing genotype data. PLoS Genetics 6: e101096.
Using Biological Knowledge To Discover Higher Order Interactions In Genetic Association Studies. Genet Epidemiol 34: 863-878.
Fine-mapping of breast cancer susceptibility loci characterizes genetic risk in African Americans. Human Molecular Genetics 20: 4491-4503.
A Genome-wide Scan for Breast Cancer Risk Haplotypes among African American Women. PLOS ONE 8, e57298.
A genome-wide association study of breast cancer in women of African ancestry. Hum Genet 132: 39-48.
Genome-wide testing of putative functional exonic variants in relationship with breast and prostate cancer risk in a multiethnic population. PLOS Genetics, 9, e1003419.

Symposium Abstract (2010)

A great deal of research has focused on how genetics affect disease susceptibility, including breast cancer. Many studies collect genetic data to compare people with a disease (cases) and those free of that disease (controls). After such a study is completed, a great deal of data has been generated which raises the question: can we reuse genetic data from participants genotyped as controls from other studies, or does each new study needs its own controls?

Given the huge investments made recently in large scale genotyping of cases and controls for various diseases, the ability to leverage existing data would represent an enormous savings of money and time. We are studying whether studies where cases and controls are sampled differently will give correct answers and are as powerful statistically as when new control data is also genotyped. This question is especially important in understanding the genetic causes of disease in as yet relatively understudied population groups, such as African Americans, in order to speed up progress as much as possible.

We give theoretical results about the power of studies that reuse existing control genotypes based on statistical considerations. We also provide analysis of real data from a major study of the genetic causes of breast cancer in African American women in order to shed practical light upon this issue.

Genome-Wide Testing of Putative Functional Exonic Variants in Relationship with Breast and Prostate Cancer Risk in a Multiethnic Population
Periodical:PLoS Genetics
Index Medicus: PLoS Genet
Authors: Haiman CA, Han Y, Feng Y, Xia L, Hsu C, et al
Yr: 2013 Vol: 9 Nbr: 3 Abs: Pg:e1003419

A Genome-wide Scan for Breast Cancer Risk Haplotypes among African American Women
Periodical:PLOS One
Index Medicus: PLOS One
Authors: Song C, Stram DO, et al
Yr: 2013 Vol: 8 Nbr: Abs: e57298 Pg:

A genome-wide association study of breast cancer in women of African ancestry
Periodical:Human Genetics
Index Medicus:
Authors: Chen F, Chen GK, Stram DO, Millikan RC, Ambrosone CB, et al.
Yr: 2013 Vol: 132 Nbr: Abs: Pg:39-48

Methodological Considerations in Estimation of Phenotype Heritability Using GenomeWide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults
Periodical:PLOS One
Index Medicus: PLOS One
Authors: Chen F, He J, Zhang J, Chen GK, Thomas V, Ambrosone CB, et al
Yr: 2015 Vol: 10 Nbr: 6 Abs: Pg:e013116