31
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Determining the genetic basis of anthracycline-cardiotoxicity by molecular response QTL mapping in induced cardiomyocytes

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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 24 hr 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 quantitative trait loci (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.

          eLife digest

          Many cancers, including leukaemia, lymphoma and breast cancer, are treated with potent chemotherapy drugs such as anthracyclines. However, anthracyclines have strong side effects known as anthracycline cardiotoxicity, which affect the health of the heart. Almost half of the patients given high doses of anthracyclines develop chronic heart failure.

          While anthracycline cardiotoxicity is very common, people’s genes may contribute to how sensitive they are to these drugs but it is not understood which genes can cause this effect. Previous studies using only a small number of participants have not been able to pin down the genetic factors that make some patients respond well to anthracyclines, and others prone to developing heart failure when taking these drugs.

          To find out which genes affect anthracycline cardiotoxicity, Knowles, Burrows et al. transformed blood cells from 45 individuals into stem cells, which were then developed into heart muscle cells. Then, the activity of genes was analyzed by measuring the amount of RNA (the template molecules used to make proteins) produced by those genes.

          After the cells had been exposed for 24 hours to the anthracycline drug doxorubicin, hundreds of gene activity differences could be found in the heart muscle cells between individuals. Some of these differences were linked to poorer health of the cells after treatment with the drug. As a result, a number of genetic variants that could predispose patients to the side effects of doxorubicin were discovered. The experiments also revealed how doxorubicin disrupts an important process that separates ‘junk’ parts of the RNA from the parts that are used as a template for proteins.

          Being able to predict who is likely to be sensitive to drugs such as doxorubicin could help doctors to tailor chemotherapy treatments more effectively, minimising the risk of heart failure. In future, larger studies could lead to accurate predictions of a patient’s response to a particular chemotherapy drug to personalize their cancer treatment.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

          , , (2013)
          Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found

            Common genetic variation drives molecular heterogeneity in human iPSCs

            Induced pluripotent stem cell (iPSC) technology has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterisation of many existing iPSC lines limits their potential use for research and therapy. Here, we describe the systematic generation, genotyping and phenotyping of 711 iPSC lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative (HipSci: http://www.hipsci.org). Our study outlines the major sources of genetic and phenotypic variation in iPSCs and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPSC phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of rare, genomic copy number mutations that are repeatedly observed in iPSC reprogramming and present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              WASP: allele-specific software for robust molecular quantitative trait locus discovery

              Allele-specific sequencing reads provide a powerful signal for identifying molecular quantitative trait loci (QTLs), however they are challenging to analyze and prone to technical artefacts. Here we describe WASP, a suite of tools for unbiased allele-specific read mapping and discovery of molecular QTLs. Using simulated reads, RNA-seq reads and ChIP-seq reads, we demonstrate that WASP has a low error rate and is far more powerful than existing QTL mapping approaches.
                Bookmark

                Author and article information

                Contributors
                Role: Reviewing Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                08 May 2018
                2018
                : 7
                : e33480
                Affiliations
                [1 ]deptDepartment of Genetics Stanford University StanfordUnited States
                [2 ]deptDepartment of Radiology Stanford University StanfordUnited States
                [3 ]deptDepartment of Human Genetics University of Chicago ChicagoUnited States
                [4 ]deptDepartment of Health Sciences Research Mayo Clinic JacksonvilleUnited States
                [5 ]deptDepartment of Cancer Biology Mayo Clinic JacksonvilleUnited States
                [6 ]deptDepartment of Biology Stanford University StanfordUnited States
                [7 ]deptHoward Hughes Medical Institute Stanford University StanfordUnited States
                [8 ]deptDepartment of Medicine University of Chicago ChicagoUnited States
                [9]Oxford University United Kingdom
                [10]Oxford University United Kingdom
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-7408-146X
                http://orcid.org/0000-0003-2634-9879
                https://orcid.org/0000-0002-8828-5236
                https://orcid.org/0000-0001-8284-8926
                Article
                33480
                10.7554/eLife.33480
                6010343
                29737278
                43549894-1201-4a58-a281-a5b41133fcc8
                © 2018, Knowles et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 11 November 2017
                : 30 April 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: HL092206
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: HG008140
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: HG009431
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: TL1 TR 432-7
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Genetics and Genomics
                Custom metadata
                Genetic variants that modulate transcriptomic response to doxorubicin in human iPSC-derived cardiomyocytes are predictive of cardiac damage and in vivo sensitivity to anthracycline cardiotoxicity.

                Life sciences
                anthracycline-induced toxicity,response expression qtl,ipsc-derived differentiated cells,doxorubicin,oxidative damage,human

                Comments

                Comment on this article