TY - JOUR
T1 - MiXcan
T2 - a framework for cell-type-aware transcriptome-wide association studies with an application to breast cancer
AU - Song, Xiaoyu
AU - Ji, Jiayi
AU - Rothstein, Joseph H.
AU - Alexeeff, Stacey E.
AU - Sakoda, Lori C.
AU - Sistig, Adriana
AU - Achacoso, Ninah
AU - Jorgenson, Eric
AU - Whittemore, Alice S.
AU - Klein, Robert J.
AU - Habel, Laurel A.
AU - Wang, Pei
AU - Sieh, Weiva
N1 - Funding Information:
This study was supported by the National Institutes of Health R01CA237541 (W.S., L.A.H., P.W.), R01CA244948 (R.J.K.), R01CA264987 (W.S., L.A.H.), R03AG075567 (X.S.), U24CA210993 (P.W.), U24CA271114 (P.W.), and P30CA196521 (X.S.). The authors acknowledge the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. The BCAC breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec and grant PSR-SIIRI-701, the National Institutes of Health (U19CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and the European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935); all studies and funders are listed11. The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The results published here are in whole or part based upon data generated by the TCGA Research Network.
Funding Information:
This study was supported by the National Institutes of Health R01CA237541 (W.S., L.A.H., P.W.), R01CA244948 (R.J.K.), R01CA264987 (W.S., L.A.H.), R03AG075567 (X.S.), U24CA210993 (P.W.), U24CA271114 (P.W.), and P30CA196521 (X.S.). The authors acknowledge the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. The BCAC breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec and grant PSR-SIIRI-701, the National Institutes of Health (U19CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and the European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935); all studies and funders are listed. The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The results published here are in whole or part based upon data generated by the TCGA Research Network.
Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85146784678&partnerID=8YFLogxK
U2 - 10.1038/s41467-023-35888-4
DO - 10.1038/s41467-023-35888-4
M3 - Article
C2 - 36690614
AN - SCOPUS:85146784678
SN - 2041-1723
VL - 14
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 377
ER -