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A framework for transcriptome-wide association studies in breast cancer in diverse study populations
by
García-Closas, Montserrat
, Bhattacharya, Arjun
, Troester, Melissa A.
, Perou, Charles M.
, Love, Michael I.
, Olshan, Andrew F.
in
African Americans
/ Animal Genetics and Genomics
/ Binding sites
/ Bioinformatics
/ Biomedical and Life Sciences
/ Black or African American - genetics
/ Breast cancer
/ breast neoplasms
/ Breast Neoplasms - ethnology
/ Breast Neoplasms - genetics
/ breasts
/ Evolutionary Biology
/ Expression quantitative trait loci (eQTL)
/ Female
/ Gene expression
/ Gene loci
/ genetic variation
/ genome
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genome-Wide Association Study - standards
/ Genomes
/ germ cells
/ Human Genetics
/ Humans
/ Life Sciences
/ Microbial Genetics and Genomics
/ Minority & ethnic groups
/ Plant Genetics and Genomics
/ Polygenic traits
/ Polymorphism, Genetic
/ Population studies
/ Quantitative Trait Loci
/ quantitative traits
/ Reproducibility of Results
/ Studies
/ Survival
/ Transcription factors
/ Transcriptome
/ Transcriptome-wide analysis (TWAS)
/ Womens health
2020
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A framework for transcriptome-wide association studies in breast cancer in diverse study populations
by
García-Closas, Montserrat
, Bhattacharya, Arjun
, Troester, Melissa A.
, Perou, Charles M.
, Love, Michael I.
, Olshan, Andrew F.
in
African Americans
/ Animal Genetics and Genomics
/ Binding sites
/ Bioinformatics
/ Biomedical and Life Sciences
/ Black or African American - genetics
/ Breast cancer
/ breast neoplasms
/ Breast Neoplasms - ethnology
/ Breast Neoplasms - genetics
/ breasts
/ Evolutionary Biology
/ Expression quantitative trait loci (eQTL)
/ Female
/ Gene expression
/ Gene loci
/ genetic variation
/ genome
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genome-Wide Association Study - standards
/ Genomes
/ germ cells
/ Human Genetics
/ Humans
/ Life Sciences
/ Microbial Genetics and Genomics
/ Minority & ethnic groups
/ Plant Genetics and Genomics
/ Polygenic traits
/ Polymorphism, Genetic
/ Population studies
/ Quantitative Trait Loci
/ quantitative traits
/ Reproducibility of Results
/ Studies
/ Survival
/ Transcription factors
/ Transcriptome
/ Transcriptome-wide analysis (TWAS)
/ Womens health
2020
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A framework for transcriptome-wide association studies in breast cancer in diverse study populations
by
García-Closas, Montserrat
, Bhattacharya, Arjun
, Troester, Melissa A.
, Perou, Charles M.
, Love, Michael I.
, Olshan, Andrew F.
in
African Americans
/ Animal Genetics and Genomics
/ Binding sites
/ Bioinformatics
/ Biomedical and Life Sciences
/ Black or African American - genetics
/ Breast cancer
/ breast neoplasms
/ Breast Neoplasms - ethnology
/ Breast Neoplasms - genetics
/ breasts
/ Evolutionary Biology
/ Expression quantitative trait loci (eQTL)
/ Female
/ Gene expression
/ Gene loci
/ genetic variation
/ genome
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genome-Wide Association Study - standards
/ Genomes
/ germ cells
/ Human Genetics
/ Humans
/ Life Sciences
/ Microbial Genetics and Genomics
/ Minority & ethnic groups
/ Plant Genetics and Genomics
/ Polygenic traits
/ Polymorphism, Genetic
/ Population studies
/ Quantitative Trait Loci
/ quantitative traits
/ Reproducibility of Results
/ Studies
/ Survival
/ Transcription factors
/ Transcriptome
/ Transcriptome-wide analysis (TWAS)
/ Womens health
2020
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A framework for transcriptome-wide association studies in breast cancer in diverse study populations
Journal Article
A framework for transcriptome-wide association studies in breast cancer in diverse study populations
2020
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Overview
Background
The relationship between germline genetic variation and breast cancer survival is largely unknown, especially in understudied minority populations who often have poorer survival. Genome-wide association studies (GWAS) have interrogated breast cancer survival but often are underpowered due to subtype heterogeneity and clinical covariates and detect loci in non-coding regions that are difficult to interpret. Transcriptome-wide association studies (TWAS) show increased power in detecting functionally relevant loci by leveraging expression quantitative trait loci (eQTLs) from external reference panels in relevant tissues. However, ancestry- or race-specific reference panels may be needed to draw correct inference in ancestrally diverse cohorts. Such panels for breast cancer are lacking.
Results
We provide a framework for TWAS for breast cancer in diverse populations, using data from the Carolina Breast Cancer Study (CBCS), a population-based cohort that oversampled black women. We perform eQTL analysis for 406 breast cancer-related genes to train race-stratified predictive models of tumor expression from germline genotypes. Using these models, we impute expression in independent data from CBCS and TCGA, accounting for sampling variability in assessing performance. These models are not applicable across race, and their predictive performance varies across tumor subtype. Within CBCS (
N
= 3,828), at a false discovery-adjusted significance of 0.10 and stratifying for race, we identify associations in black women near
AURKA
,
CAPN13
,
PIK3CA
, and
SERPINB5
via TWAS that are underpowered in GWAS.
Conclusions
We show that carefully implemented and thoroughly validated TWAS is an efficient approach for understanding the genetics underpinning breast cancer outcomes in diverse populations.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
/ Animal Genetics and Genomics
/ Biomedical and Life Sciences
/ Black or African American - genetics
/ Breast Neoplasms - ethnology
/ breasts
/ Expression quantitative trait loci (eQTL)
/ Female
/ genome
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genome-Wide Association Study - standards
/ Genomes
/ Humans
/ Microbial Genetics and Genomics
/ Studies
/ Survival
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