13
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genome-wide association analysis of chronic lymphocytic leukaemia, Hodgkin lymphoma and multiple myeloma identifies pleiotropic risk loci

      research-article
      1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , 2 , 3 , 1 , 4 , 5 , 6 , 7 , 7 , 8 , 8 , 8 , 9 , 4 , 10 , 11 , 12 , 12 , 13 , 14 , 13 , 13 ,   13 , 15 , 16 , 15 , 17 , 18 , 18 , 4 , 1 , 19 , 20 , 21 , 2 , 3 , 13 , 14 , a , 1 , 2
      Scientific Reports
      Nature Publishing Group

      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

          B-cell malignancies (BCM) originate from the same cell of origin, but at different maturation stages and have distinct clinical phenotypes. Although genetic risk variants for individual BCMs have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. We explored genome-wide association studies of chronic lymphocytic leukaemia (CLL, N = 1,842), Hodgkin lymphoma (HL, N = 1,465) and multiple myeloma (MM, N = 3,790). We identified a novel pleiotropic risk locus at 3q22.2 ( NCK1, rs11715604, P = 1.60 × 10 −9) with opposing effects between CLL ( P = 1.97 × 10 −8) and HL ( P = 3.31 × 10 −3). Eight established non-HLA risk loci showed pleiotropic associations. Within the HLA region, Ser37 + Phe37 in HLA-DRB1 ( P = 1.84 × 10 −12) was associated with increased CLL and HL risk ( P = 4.68 × 10 −12), and reduced MM risk ( P = 1.12 × 10 −2), and Gly70 in HLA-DQB1 ( P = 3.15 × 10 −10) showed opposing effects between CLL ( P = 3.52 × 10 −3) and HL ( P = 3.41 × 10 −9). By integrating eQTL, Hi-C and ChIP-seq data, we show that the pleiotropic risk loci are enriched for B-cell regulatory elements, as well as an over-representation of binding of key B-cell transcription factors. These data identify shared biological pathways influencing the development of CLL, HL and MM. The identification of these risk loci furthers our understanding of the aetiological basis of BCMs.

          Related collections

          Most cited references59

          • Record: found
          • Abstract: found
          • Article: not found

          The molecular classification of multiple myeloma.

          To better define the molecular basis of multiple myeloma (MM), we performed unsupervised hierarchic clustering of mRNA expression profiles in CD138-enriched plasma cells from 414 newly diagnosed patients who went on to receive high-dose therapy and tandem stem cell transplants. Seven disease subtypes were validated that were strongly influenced by known genetic lesions, such as c-MAF- and MAFB-, CCND1- and CCND3-, and MMSET-activating translocations and hyperdiploidy. Indicative of the deregulation of common pathways by gene orthologs, common gene signatures were observed in cases with c-MAF and MAFB activation and CCND1 and CCND3 activation, the latter consisting of 2 subgroups, one characterized by expression of the early B-cell markers CD20 and PAX5. A low incidence of focal bone disease distinguished one and increased expression of proliferation-associated genes of another novel subgroup. Comprising varying fractions of each of the other 6 subgroups, the proliferation subgroup dominated at relapse, suggesting that this signature is linked to disease progression. Proliferation and MMSET-spike groups were characterized by significant overexpression of genes mapping to chromosome 1q, and both exhibited a poor prognosis relative to the other groups. A subset of cases with a predominating myeloid gene expression signature, excluded from the profiling analyses, had more favorable baseline characteristics and superior prognosis to those lacking this signature.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Genome-wide association study identifies five new breast cancer susceptibility loci.

            Breast cancer is the most common cancer in women in developed countries. To identify common breast cancer susceptibility alleles, we conducted a genome-wide association study in which 582,886 SNPs were genotyped in 3,659 cases with a family history of the disease and 4,897 controls. Promising associations were evaluated in a second stage, comprising 12,576 cases and 12,223 controls. We identified five new susceptibility loci, on chromosomes 9, 10 and 11 (P = 4.6 x 10(-7) to P = 3.2 x 10(-15)). We also identified SNPs in the 6q25.1 (rs3757318, P = 2.9 x 10(-6)), 8q24 (rs1562430, P = 5.8 x 10(-7)) and LSP1 (rs909116, P = 7.3 x 10(-7)) regions that showed more significant association with risk than those reported previously. Previously identified breast cancer susceptibility loci were also found to show larger effect sizes in this study of familial breast cancer cases than in previous population-based studies, consistent with polygenic susceptibility to the disease.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A genome-wide association scan of tag SNPs identifies a susceptibility variant for colorectal cancer at 8q24.21.

              Much of the variation in inherited risk of colorectal cancer (CRC) is probably due to combinations of common low risk variants. We conducted a genome-wide association study of 550,000 tag SNPs in 930 familial colorectal tumor cases and 960 controls. The most strongly associated SNP (P = 1.72 x 10(-7), allelic test) was rs6983267 at 8q24.21. To validate this finding, we genotyped rs6983267 in three additional CRC case-control series (4,361 affected individuals and 3,752 controls; 1,901 affected individuals and 1,079 controls; 1,072 affected individuals and 415 controls) and replicated the association, providing P = 1.27 x 10(-14) (allelic test) overall, with odds ratios (ORs) of 1.27 (95% confidence interval (c.i.): 1.16-1.39) and 1.47 (95% c.i.: 1.34-1.62) for heterozygotes and rare homozygotes, respectively. Analyses based on 1,477 individuals with colorectal adenoma and 2,136 controls suggest that susceptibility to CRC is mediated through development of adenomas (OR = 1.21, 95% c.i.: 1.10-1.34; P = 6.89 x 10(-5)). These data show that common, low-penetrance susceptibility alleles predispose to colorectal neoplasia.
                Bookmark

                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                23 January 2017
                2017
                : 7
                : 41071
                Affiliations
                [1 ]Division of Genetics and Epidemiology, The Institute of Cancer Research , London, UK
                [2 ]Division of Molecular Pathology, The Institute of Cancer Research , London, UK
                [3 ]Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences , Little Rock, USA
                [4 ]Northern Institute for Cancer Research, Newcastle University , Newcastle upon Tyne, UK
                [5 ]Department of Haematology, Royal Victoria Infirmary , Newcastle upon Tyne, UK
                [6 ]Department of Haematology, Queen Elizabeth Hospital , Gateshead, Newcastle upon Tyne, UK
                [7 ]Department of Molecular and Clinical Cancer Medicine, University of Liverpool , Liverpool, UK
                [8 ]Queens Centre for Haematology and Oncology, Castle Hill Hospital, Hull and East Yorkshire NHS Trust , UK
                [9 ]Department of Haematology, Birmingham Heartlands Hospital , Birmingham, UK
                [10 ]Department of Haematology, School of Medicine, Cardiff University , Cardiff, UK
                [11 ]Cardiff and Vale National Health Service Trust, Heath Park , Cardiff, UK
                [12 ]Department of Internal Medicine, University Hospital of Cologne , Cologne, Germany
                [13 ]Division of Molecular Genetic Epidemiology, German Cancer Research Centre , Heidelberg, Germany
                [14 ]Centre for Primary Health Care Research, Lund University , Malmö, Sweden
                [15 ]Institute of Human Genetics, University of Bonn , Germany
                [16 ]Division of Medical Genetics, Department of Biomedicine, University of Basel , Switzerland
                [17 ]Department of Genomics, Life & Brain Center, University of Bonn , Germany
                [18 ]University of Duisburg–Essen , Essen, Germany
                [19 ]Division of Breast Cancer Research, The Institute of Cancer Research , London, UK
                [20 ]Department of Internal Medicine V, University of Heidelberg , Heidelberg, Germany
                [21 ]National Center of Tumor Diseases , Heidelberg, Germany
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep41071
                10.1038/srep41071
                5253627
                74fe747e-a0bb-4fbc-a1b9-49054c18207f
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 05 October 2016
                : 14 December 2016
                Categories
                Article

                Uncategorized
                Uncategorized

                Comments

                Comment on this article