MiXcan: A Framework for Cell-Type-Aware Transcriptome-Wide Association Studies With an Application to Breast Cancer

Authors

Xiaoyu Song
Jiayi Ji
Joseph H Rothstein
Stacey E Alexeeff
Lori C Sakoda
Adriana Sistig
Ninah Achacoso
Eric Jorgenson
Alice S Whittemore
Robert J Klein
Laurel A Habel
Pei Wang
Weiva Sieh

Publication Date

1-23-2023

Journal

Nature Communications

Abstract

Human bulk tissue samples comprise multiple cell types with diverse roles in disease etiology. Conventional transcriptome-wide association study approaches predict genetically regulated gene expression at the tissue level, without considering cell-type heterogeneity, and test associations of predicted tissue-level expression with disease. Here we develop MiXcan, a cell-type-aware transcriptome-wide association study approach that predicts cell-type-level expression, identifies disease-associated genes via combination of cell-type-level association signals for multiple cell types, and provides insight into the disease-critical cell type. As a proof of concept, we conducted cell-type-aware analyses of breast cancer in 58,648 women and identified 12 transcriptome-wide significant genes using MiXcan compared with only eight genes using conventional approaches. Importantly, MiXcan identified genes with distinct associations in mammary epithelial versus stromal cells, including three new breast cancer susceptibility genes. These findings demonstrate that cell-type-aware transcriptome-wide analyses can reveal new insights into the genetic and cellular etiology of breast cancer and other diseases.

Keywords

Female, Humans, Transcriptome, Breast Neoplasms, Gene Expression Profiling, Breast, Genome-Wide Association Study, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide

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Associated Data

PMID: 36690614