Common variation at 3p22.1 and 7p15.3 influences multiple myeloma risk
Richard Houlston, Gareth Morgan, Kari Hemminki and colleagues report the results of a genome-wide association study of multiple myeloma. They identify two regions influencing susceptibility to this hematological malignancy. To identify risk variants for multiple myeloma, we conducted a genome-wide a...
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| Published in | Nature genetics Vol. 44; no. 1; pp. 58 - 61 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Nature Publishing Group US
01.01.2012
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Richard Houlston, Gareth Morgan, Kari Hemminki and colleagues report the results of a genome-wide association study of multiple myeloma. They identify two regions influencing susceptibility to this hematological malignancy.
To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in
ULK4
; odds ratio (OR) = 1.32;
P
= 7.47 × 10
−9
) and 7p15.3 (rs4487645, OR = 1.38;
P
= 3.33 × 10
−15
). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29;
P
= 1.22 × 10
−7
). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights. |
|---|---|
| AbstractList | To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 x 10 super(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 x 10 super(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 x 10 super(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights. To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 × 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights.To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 × 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights. To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 x 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 x 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 x 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights. To identify risk variants for multiple myeloma (MM), we conducted a genome-wide association study totaling of 1,675 MM cases and 5,903 controls. We identified risk loci for MM at 3p22.1 (rs1052501, ULK4 ; odds ratio [OR]=1.32; P =7.47x10 -9 ) and 7p15.3 (rs4487645, OR=1.38; P =3.33x10 -15 ). In addition, we observed a promising association at 2p23.3 (rs6746082, OR=1.29; P =1.22x10 -7 ). Our study reports previously unidentified genomic regions associated with MM risk that may lead to new etiological insights. To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 × 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights. To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 × 10^sup -9^) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10^sup -15^). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10^sup -7^). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights. [PUBLICATION ABSTRACT] Richard Houlston, Gareth Morgan, Kari Hemminki and colleagues report the results of a genome-wide association study of multiple myeloma. They identify two regions influencing susceptibility to this hematological malignancy. To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4 ; odds ratio (OR) = 1.32; P = 7.47 × 10 −9 ) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10 −15 ). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10 −7 ). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights. |
| Author | Mühleisen, Thomas W Jackson, Graham H Hemminki, Kari Dobbins, Sara E Houlston, Richard S Weinhold, Niels Child, J Anthony Goldschmidt, Hartmut Moebus, Susanne Nöthen, Markus M Chubb, Daniel Jauch, Anna Tomlinson, Ian P Lloyd, Amy Morgan, Gareth J Olver, Bianca Johnson, David C Ross, Fiona M Gregory, Walter A Försti, Asta Walker, Brian A Neben, Kai Broderick, Peter Hoffmann, Per Davies, Faith E Ma, Yussanne P |
| AuthorAffiliation | 10 Royal Victoria Infirmary, Newcastle-on-Tyne, UK 4 German Cancer Research Center, Heidelberg, Germany 3 Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany 6 German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany 8 University of Leeds, Leeds, UK 2 Haemato-Oncology Research Unit, Division of Molecular Pathology, Institute of Cancer Research, Surrey, UK 5 Institute of Human Genetics, University of Bonn, Germany 13 National Centre of Tumour Diseases, Heidelberg, Germany 7 Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Germany 11 Institute of Human Genetics, University of Heidelberg, Germany 12 Molecular and Population Genetics, Wellcome Trust Centre for Human Genetics, Oxford, OX3 7BN, UK 14 Center for Primary Health Care Research, Lund University, Malmo, Sweden 9 Cytogenetics Group, Wessex Regional Cytogenetic Laboratory, Salisbury, UK 1 Molecular and Population Genetics, Division of Geneti |
| AuthorAffiliation_xml | – name: 12 Molecular and Population Genetics, Wellcome Trust Centre for Human Genetics, Oxford, OX3 7BN, UK – name: 9 Cytogenetics Group, Wessex Regional Cytogenetic Laboratory, Salisbury, UK – name: 2 Haemato-Oncology Research Unit, Division of Molecular Pathology, Institute of Cancer Research, Surrey, UK – name: 14 Center for Primary Health Care Research, Lund University, Malmo, Sweden – name: 10 Royal Victoria Infirmary, Newcastle-on-Tyne, UK – name: 13 National Centre of Tumour Diseases, Heidelberg, Germany – name: 4 German Cancer Research Center, Heidelberg, Germany – name: 5 Institute of Human Genetics, University of Bonn, Germany – name: 3 Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany – name: 11 Institute of Human Genetics, University of Heidelberg, Germany – name: 7 Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Germany – name: 1 Molecular and Population Genetics, Division of Genetics and Epidemiology, Institute of Cancer Research, Surrey, UK – name: 8 University of Leeds, Leeds, UK – name: 6 German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany |
| Author_xml | – sequence: 1 givenname: Peter surname: Broderick fullname: Broderick, Peter organization: Division of Genetics and Epidemiology, Molecular and Population Genetics, Institute of Cancer Research – sequence: 2 givenname: Daniel surname: Chubb fullname: Chubb, Daniel organization: Division of Genetics and Epidemiology, Molecular and Population Genetics, Institute of Cancer Research – sequence: 3 givenname: David C surname: Johnson fullname: Johnson, David C organization: Division of Molecular Pathology, Haemato-Oncology Research Unit, Institute of Cancer Research – sequence: 4 givenname: Niels surname: Weinhold fullname: Weinhold, Niels organization: Department of Internal Medicine V, University of Heidelberg – sequence: 5 givenname: Asta surname: Försti fullname: Försti, Asta organization: German Cancer Research Center – sequence: 6 givenname: Amy surname: Lloyd fullname: Lloyd, Amy organization: Division of Genetics and Epidemiology, Molecular and Population Genetics, Institute of Cancer Research – sequence: 7 givenname: Bianca surname: Olver fullname: Olver, Bianca organization: Division of Genetics and Epidemiology, Molecular and Population Genetics, Institute of Cancer Research – sequence: 8 givenname: Yussanne P surname: Ma fullname: Ma, Yussanne P organization: Division of Genetics and Epidemiology, Molecular and Population Genetics, Institute of Cancer Research – sequence: 9 givenname: Sara E surname: Dobbins fullname: Dobbins, Sara E organization: Division of Genetics and Epidemiology, Molecular and Population Genetics, Institute of Cancer Research – sequence: 10 givenname: Brian A surname: Walker fullname: Walker, Brian A organization: Division of Molecular Pathology, Haemato-Oncology Research Unit, Institute of Cancer Research – sequence: 11 givenname: Faith E surname: Davies fullname: Davies, Faith E organization: Division of Molecular Pathology, Haemato-Oncology Research Unit, Institute of Cancer Research – sequence: 12 givenname: Walter A surname: Gregory fullname: Gregory, Walter A organization: Clinical Trials Research Unit, University of Leeds – sequence: 13 givenname: J Anthony surname: Child fullname: Child, J Anthony organization: Clinical Trials Research Unit, University of Leeds – sequence: 14 givenname: Fiona M surname: Ross fullname: Ross, Fiona M organization: Cytogenetics Group, Wessex Regional Cytogenetic Laboratory – sequence: 15 givenname: Graham H surname: Jackson fullname: Jackson, Graham H organization: Royal Victoria Infirmary – sequence: 16 givenname: Kai surname: Neben fullname: Neben, Kai organization: Department of Internal Medicine V, University of Heidelberg – sequence: 17 givenname: Anna surname: Jauch fullname: Jauch, Anna organization: Institute of Human Genetics, University of Heidelberg – sequence: 18 givenname: Per surname: Hoffmann fullname: Hoffmann, Per organization: Institute of Human Genetics, University of Bonn – sequence: 19 givenname: Thomas W surname: Mühleisen fullname: Mühleisen, Thomas W organization: Institute of Human Genetics, University of Bonn – sequence: 20 givenname: Markus M surname: Nöthen fullname: Nöthen, Markus M organization: Institute of Human Genetics, University of Bonn, German Center for Neurodegenerative Diseases (DZNE) – sequence: 21 givenname: Susanne surname: Moebus fullname: Moebus, Susanne organization: Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg–Essen – sequence: 22 givenname: Ian P surname: Tomlinson fullname: Tomlinson, Ian P organization: Molecular and Population Genetics, Wellcome Trust Centre for Human Genetics – sequence: 23 givenname: Hartmut surname: Goldschmidt fullname: Goldschmidt, Hartmut organization: Department of Internal Medicine V, University of Heidelberg, National Centre of Tumour Diseases – sequence: 24 givenname: Kari surname: Hemminki fullname: Hemminki, Kari organization: German Cancer Research Center, Center for Primary Health Care Research, Lund University – sequence: 25 givenname: Gareth J surname: Morgan fullname: Morgan, Gareth J organization: Division of Molecular Pathology, Haemato-Oncology Research Unit, Institute of Cancer Research – sequence: 26 givenname: Richard S surname: Houlston fullname: Houlston, Richard S email: richard.houlston@icr.ac.uk organization: Division of Genetics and Epidemiology, Molecular and Population Genetics, Institute of Cancer Research, Division of Molecular Pathology, Haemato-Oncology Research Unit, Institute of Cancer Research |
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| ContentType | Journal Article |
| Copyright | Springer Nature America, Inc. 2011 2015 INIST-CNRS Copyright Nature Publishing Group Jan 2012 |
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| CorporateAuthor | Lunds universitet Profile areas and other strong research environments Department of Clinical Sciences, Malmö Lund University Strategiska forskningsområden (SFO) EpiHealth: Epidemiology for Health Faculty of Medicine Family Medicine and Clinical Epidemiology Allmänmedicin och klinisk epidemiologi Strategic research areas (SRA) Medicinska fakulteten Profilområden och andra starka forskningsmiljöer Institutionen för kliniska vetenskaper, Malmö |
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| DOI | 10.1038/ng.993 |
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| Keywords | Immunopathology Immunoglobulinopathy Lymphoproliferative syndrome Risk Malignant hemopathy Myeloma Cancer |
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| Snippet | Richard Houlston, Gareth Morgan, Kari Hemminki and colleagues report the results of a genome-wide association study of multiple myeloma. They identify two... To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control... To identify risk variants for multiple myeloma (MM), we conducted a genome-wide association study totaling of 1,675 MM cases and 5,903 controls. We identified... |
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| SubjectTerms | 631/208/727/2000 692/699/67/1990/804 Agriculture Animal Genetics and Genomics Biological and medical sciences Biomedical and Life Sciences Biomedicine Cancer Research Case-Control Studies Chromosomes, Human, Pair 3 Chromosomes, Human, Pair 7 Colorectal cancer Confidence intervals Fundamental and applied biological sciences. Psychology Gene Function Genes Genetic Predisposition to Disease Genetic Variation Genetics of eukaryotes. Biological and molecular evolution Genome-Wide Association Study Genomes Genotype & phenotype Health Sciences Health services Hematologic and hematopoietic diseases Hospitals Human Genetics Humans Hälsovetenskap Immunodeficiencies. Immunoglobulinopathies Immunoglobulinopathies Immunopathology Kinases letter Leukemias. Malignant lymphomas. Malignant reticulosis. Myelofibrosis Medical and Health Sciences Medical research Medical sciences Medicin och hälsovetenskap Multiple myeloma Multiple Myeloma - genetics Polymorphism, Single Nucleotide Protein Serine-Threonine Kinases - genetics Quality control Risk Factors Software Studies |
| Title | Common variation at 3p22.1 and 7p15.3 influences multiple myeloma risk |
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