Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes

Abstract Background While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we pe...

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Main Authors: Molly Went, Ben Kinnersley, Amit Sud, David C. Johnson, Niels Weinhold, Asta Försti, Mark van Duin, Giulia Orlando, Jonathan S. Mitchell, Rowan Kuiper, Brian A. Walker, Walter M. Gregory, Per Hoffmann, Graham H. Jackson, Markus M. Nöthen, Miguel Inacio da Silva Filho, Hauke Thomsen, Annemiek Broyl, Faith E. Davies, Unnur Thorsteinsdottir, Markus Hansson, Martin Kaiser, Pieter Sonneveld, Hartmut Goldschmidt, Kari Stefansson, Kari Hemminki, Björn Nilsson, Gareth J. Morgan, Richard S. Houlston
Format: Article
Language:English
Published: BMC 2019-08-01
Series:Human Genomics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40246-019-0231-5
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spelling doaj-921d6df1bf474729aae772a11dae54202020-11-25T03:49:15ZengBMCHuman Genomics1479-73642019-08-011311810.1186/s40246-019-0231-5Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genesMolly Went0Ben Kinnersley1Amit Sud2David C. Johnson3Niels Weinhold4Asta Försti5Mark van Duin6Giulia Orlando7Jonathan S. Mitchell8Rowan Kuiper9Brian A. Walker10Walter M. Gregory11Per Hoffmann12Graham H. Jackson13Markus M. Nöthen14Miguel Inacio da Silva Filho15Hauke Thomsen16Annemiek Broyl17Faith E. Davies18Unnur Thorsteinsdottir19Markus Hansson20Martin Kaiser21Pieter Sonneveld22Hartmut Goldschmidt23Kari Stefansson24Kari Hemminki25Björn Nilsson26Gareth J. Morgan27Richard S. Houlston28Division of Genetics and Epidemiology, The Institute of Cancer ResearchDivision of Genetics and Epidemiology, The Institute of Cancer ResearchDivision of Genetics and Epidemiology, The Institute of Cancer ResearchDivision of Molecular Pathology, The Institute of Cancer ResearchDepartment of Internal Medicine V, University of HeidelbergGerman Cancer Research CenterDepartment of Hematology, Erasmus MC Cancer InstituteDivision of Genetics and Epidemiology, The Institute of Cancer ResearchDivision of Genetics and Epidemiology, The Institute of Cancer ResearchDepartment of Hematology, Erasmus MC Cancer InstituteMyeloma Institute for Research and Therapy, University of Arkansas for Medical SciencesClinical Trials Research Unit, University of LeedsInstitute of Human Genetics, University of BonnRoyal Victoria InfirmaryInstitute of Human Genetics, University of BonnGerman Cancer Research CenterGerman Cancer Research CenterDepartment of Hematology, Erasmus MC Cancer InstituteMyeloma Institute for Research and Therapy, University of Arkansas for Medical SciencesdeCODE GeneticsHematology Clinic, Skåne University HospitalDivision of Molecular Pathology, The Institute of Cancer ResearchMyeloma Institute for Research and Therapy, University of Arkansas for Medical SciencesDepartment of Internal Medicine V, University of HeidelbergdeCODE GeneticsGerman Cancer Research CenterHematology and Transfusion Medicine, Department of Laboratory Medicine, BMC B13Myeloma Institute for Research and Therapy, University of Arkansas for Medical SciencesDivision of Genetics and Epidemiology, The Institute of Cancer ResearchAbstract Background While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS). Results GWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80–491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus. Conclusions Our findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.http://link.springer.com/article/10.1186/s40246-019-0231-5Genome-wide association studyGene expressionMultiple myelomaTranscriptome-wide association study
collection DOAJ
language English
format Article
sources DOAJ
author Molly Went
Ben Kinnersley
Amit Sud
David C. Johnson
Niels Weinhold
Asta Försti
Mark van Duin
Giulia Orlando
Jonathan S. Mitchell
Rowan Kuiper
Brian A. Walker
Walter M. Gregory
Per Hoffmann
Graham H. Jackson
Markus M. Nöthen
Miguel Inacio da Silva Filho
Hauke Thomsen
Annemiek Broyl
Faith E. Davies
Unnur Thorsteinsdottir
Markus Hansson
Martin Kaiser
Pieter Sonneveld
Hartmut Goldschmidt
Kari Stefansson
Kari Hemminki
Björn Nilsson
Gareth J. Morgan
Richard S. Houlston
spellingShingle Molly Went
Ben Kinnersley
Amit Sud
David C. Johnson
Niels Weinhold
Asta Försti
Mark van Duin
Giulia Orlando
Jonathan S. Mitchell
Rowan Kuiper
Brian A. Walker
Walter M. Gregory
Per Hoffmann
Graham H. Jackson
Markus M. Nöthen
Miguel Inacio da Silva Filho
Hauke Thomsen
Annemiek Broyl
Faith E. Davies
Unnur Thorsteinsdottir
Markus Hansson
Martin Kaiser
Pieter Sonneveld
Hartmut Goldschmidt
Kari Stefansson
Kari Hemminki
Björn Nilsson
Gareth J. Morgan
Richard S. Houlston
Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
Human Genomics
Genome-wide association study
Gene expression
Multiple myeloma
Transcriptome-wide association study
author_facet Molly Went
Ben Kinnersley
Amit Sud
David C. Johnson
Niels Weinhold
Asta Försti
Mark van Duin
Giulia Orlando
Jonathan S. Mitchell
Rowan Kuiper
Brian A. Walker
Walter M. Gregory
Per Hoffmann
Graham H. Jackson
Markus M. Nöthen
Miguel Inacio da Silva Filho
Hauke Thomsen
Annemiek Broyl
Faith E. Davies
Unnur Thorsteinsdottir
Markus Hansson
Martin Kaiser
Pieter Sonneveld
Hartmut Goldschmidt
Kari Stefansson
Kari Hemminki
Björn Nilsson
Gareth J. Morgan
Richard S. Houlston
author_sort Molly Went
title Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
title_short Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
title_full Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
title_fullStr Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
title_full_unstemmed Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
title_sort transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes
publisher BMC
series Human Genomics
issn 1479-7364
publishDate 2019-08-01
description Abstract Background While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS). Results GWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80–491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus. Conclusions Our findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.
topic Genome-wide association study
Gene expression
Multiple myeloma
Transcriptome-wide association study
url http://link.springer.com/article/10.1186/s40246-019-0231-5
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