Determining the genetic basis of anthracycline-cardiotoxicity by response QTL mapping in induced cardiomyocytes
Abstract
Anthracycline-induced cardiotoxicity (ACT) is a key limiting factor in setting optimal chemotherapy regimes, with almost half of patients expected to develop congestive heart failure given high doses. However, the genetic basis of sensitivity to anthracyclines remains unclear. We created a panel of iPSC-derived cardiomyocytes from 45 individuals and performed RNA-seq after 24h exposure to varying doxorubicin dosages. The transcriptomic response is substantial: the majority of genes are differentially expressed and over 6000 genes show evidence of differential splicing, the later driven by reduced splicing fidelity in the presence of doxorubicin. We show that inter-individual variation in transcriptional response is predictive of in vitro cell damage, which in turn is associated with in vivo ACT risk. We detect 447 response-expression QTLs and 42 response-splicing QTLs, which are enriched in lower ACT GWAS p-values, supporting the in vivo relevance of our map of genetic regulation of cellular response to anthracyclines.
Data availability
All the custom analysis scripts used for this project are available at https://github.com/davidaknowles/dox (Knowles and Blischak, 2017). The suez response eQTL mapping R package is available at https://github.com/davidaknowles/suez (Knowles, 2017). The following data are available as Supplementary Data: 1) differential expression cluster assignments, 2) significant (5% FDR) eQTLs and sQTLs, 3) differential splicing results, 4) levels of cardiac troponin and the predicted transcriptomic response. In addition to the Supplementary Data included with this paper, further results are hosted at Dryad (doi:10.5061/dryad.r5t8d04) including 1) gene-by-sample matrix of RNA-seq quantification (log counts per million), 2) LeafCutter intron excision quantification 3) p-values for all tested eQTLs, reQTLs, sQTLs, and rsQTLs, 4) RARG variant response and marginal trans-eQTLs, 5) RIN, RNA concentration and other technical covariates, 6) embryoid body imaging for all iPSC lines. The RNA-seq FASTQ files will be added to the dbGaP database (Tryka et al., 2014) under dbGaP accession phs000185 (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000185). The genotype data files cannot be shared because releasing genotype data from a subset of individuals in the pedigree would enable the reconstruction of genotypes of other members of the pedigree, which would violate the original protocol approved by the research ethics board (Livne et al., 2015). The summary statistics for the ACT GWAS were given to us by the authors of the study (Schneider et al., 2016; Serie et al. 2017).
-
Expression and splicing quantification, eQTLs and sQTLsAvailable at Dryad Digital Repository under a CC0 Public Domain Dedication.
Article and author information
Author details
Funding
NIH Office of the Director (HL092206)
- Yoav Gilad
Howard Hughes Medical Institute
- Jonathan K Pritchard
NIH Office of the Director (HG008140)
- Jonathan K Pritchard
NIH Office of the Director (HG009431)
- Jonathan K Pritchard
NIH Office of the Director (TL1 TR 432-7)
- Courtney K Burrows
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Human Subjects work was approved by the University of Chicago IRB (protocol 10-416-B). Written informed consent was obtained from all participants.
Copyright
© 2018, Knowles et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 4,485
- views
-
- 530
- downloads
-
- 105
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 105
- citations for umbrella DOI https://doi.org/10.7554/eLife.33480