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A Genome-Wide Meta-Analysis Yields 46 New Loci Associating with Biomarkers of Iron Homeostasis

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A Genome-Wide Meta-Analysis Yields 46 New Loci Associating with Biomarkers of Iron Homeostasis A Genome-Wide Meta-Analysis Yields 46 New Loci Associating with Biomarkers of Iron Homeostasis Bell, Steven ; Rigas, Andreas S. ; Magnusson, Magnus K. ; Ferkingstad, Egil ; Allara, Elias ; Bjornsdottir, Gyda ; Ramond, Anna ; Sørensen, Erik; Halldorsson, Gisli H. ; Paul, Dirk S. ; Burgdorf, Kristoffer Sølvsten; Eggertsson, Hanne P. ; Howson, Joanna M. M. ; Thørner, Lise W. ; Kristmundsdottir, Snaedis ; Astle, William J. ; Erikstrup, Christian; Sigurdsson, Jon K. ; Vukovic, Dragana; Dinh, Khoa M. ; Tragante, Vinicius ; Surendran, Praveen ; Pedersen, Ole Birger; Vidarsson, Brynja ; Jiang, Tao; Paarup, Helene M.; Onundarson, Pall T. ; Akbari, Parsa ; Nielsen, Kaspar René; Lund, Sigrun H. ; Juliusson, Kristinn ; Magnusson, Magnus I. ; Frigge, Michael L. ; Oddsson, Asmundur ; Olafsson, Isleifur ; Kaptoge, Stephen ; Hjalgrim, Henrik; Runarsson, Gudmundur ; Wood, Angela M. ; Jonsdottir, Ingileif ; Folkmann Hansen, Thomas; Sigurdardottir, Olof ; Stefansson, Hreinn ; Rye, David ; Andersen, Steffen; Banasik, Karina; Brunak, Søren; Burgdorf, Kristoffer ; Erikstrup, Christian; Jemec, Gregor Borut Ernst; Jennum, Poul; Johanssond, Pär I.; Nyegaard, Mette; Petersen, Mikkel; Werge, Thomas; Peters, James E. ; Westergaard, David; Holm, Hilma ; Soranzo, Nicole ; Thorleifsson, Gudmar ; Ouwehand, Willem H. ; Thorsteinsdottir, Unnur ; Roberts, David J. ; Sulem, Patrick; Butterworth, Adam S. ; Gudbjartsson, Daniel F. ; Danesh, John ; Brunak, Søren; Angelantonio, Emanuele Di ; Ullum, Henrik; Stefansson, Kari Document Version Final published version Published in: Communications Biology DOI: 10.1038/s42003-020-01575-z Publication date: 2021 License CC BY Citation for published version (APA): Bell, S., Rigas, A. S., Magnusson, M. K., Ferkingstad, E., Allara, E., Bjornsdottir, G., Ramond, A., Sørensen, E., Halldorsson, G. H., Paul, D. S., Burgdorf, K. S., Eggertsson, H. P., Howson, J. M. M., Thørner, L. W., Kristmundsdottir, S., Astle, W. J., Erikstrup, C., Sigurdsson, J. K., Vukovic, D., ... Stefansson, K. (2021). A Genome-Wide Meta-Analysis Yields 46 New Loci Associating with Biomarkers of Iron Homeostasis. Communications Biology, 4, [156]. https://doi.org/10.1038/s42003-020-01575-z Link to publication in CBS Research Portal General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. ARTICLE https://doi.org/10.1038/s42003-020-01575-z OPEN A genome-wide meta-analysis yields 46 new loci associating with biomarkers of iron homeostasis ✉ Steven Bell 1,2,35, Andreas S. Rigas3,35, Magnus K. Magnusson 4,5,35 , Egil Ferkingstad 4,35, Elias Allara 1,2,35, Gyda Bjornsdottir4, Anna Ramond1,2,6, Erik Sørensen3, Gisli H. Halldorsson 4, Dirk S. Paul 1,2, Kristoffer S. Burgdorf3, Hannes P. Eggertsson 4, Joanna M. M. Howson 2, Lise W. Thørner3, 1234567890():,; Snaedis Kristmundsdottir4, William J. Astle1,2,7,8, Christian Erikstrup 9, Jon K. Sigurdsson4, Dragana Vuckovic1,8, Khoa M. Dinh9, Vinicius Tragante 4,10, Praveen Surendran2,11, Ole B. Pedersen 12, Brynjar Vidarsson13, Tao Jiang1,2,8, Helene M. Paarup 14, Pall T. Onundarson5,15, Parsa Akbari 1,2,8, Kaspar R. Nielsen16, Sigrun H. Lund 4, Kristinn Juliusson4, Magnus I. Magnusson4, Michael L. Frigge 4, Asmundur Oddsson 4, Isleifur Olafsson17, Stephen Kaptoge1,2, Henrik Hjalgrim18, Gudmundur Runarsson13, Angela M. Wood1,2, Ingileif Jonsdottir 4,5, Thomas F. Hansen 19,20,21, Olof Sigurdardottir22, Hreinn Stefansson 4, David Rye23, DBDS Genomic Consortium*, James E. Peters2, David Westergaard 24, Hilma Holm 4, Nicole Soranzo 1,8,25, Karina Banasik 24, Gudmar Thorleifsson4, Willem H. Ouwehand 1,8,25,26, Unnur Thorsteinsdottir4,5, David J. Roberts1,27,28, Patrick Sulem 4, Adam S. Butterworth 1,2, Daniel F. Gudbjartsson 4,29, John Danesh1,2,8, Søren Brunak 24, ✉ ✉ ✉ Emanuele Di Angelantonio1,2,26,36 , Henrik Ullum3,36 & Kari Stefansson 4,5,36 Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, the UK and Denmark of blood levels of ferritin (N = 246,139), total iron binding capacity (N = 135,430), iron (N = 163,511) and transferrin saturation (N = 131,471). We found 62 inde- pendent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation. A full list of author affiliations appears at the end of the paper. COMMUNICATIONS BIOLOGY | (2021) 4:156 | https://doi.org/10.1038/s42003-020-01575-z | www.nature.com/commsbio 1 ARTICLE COMMUNICATIONS BIOLOGY | https://doi.org/10.1038/s42003-020-01575-z ron is an essential element for a wide variety of metabolic pro- Results Icesses such as oxygen transport, cellular respiration, and redox Overview. We performed a meta-analysis of four iron-related reactions in numerous metabolic pathways. For this reason, iron biomarkers: ferritin (N = 246,139), serum iron (N = 163,511), homeostasis is tightly regulated on cellular and systemic levels to TIBC (N = 135,430), and TSAT (N = 131,471), combining GWAS ensure a balance between uptake, transport, storage, and utilization. results from Iceland, the UK, and Denmark (Fig. 1, Supplementary Iron deficiency is one of the five leading causes of disability world- Data 1). We found associations with iron homeostasis biomarkers wide, especially among children and women of childbearing age1,2. represented by 62 sequence variants at 56 loci, of which 46 have Similarly, iron overload is associated with an increased risk of several not been reported in the previous GWAS on iron homeostasis and major chronic conditions, including diabetes and liver disease1,3. are therefore considered novel (Table 1, Table 2, Fig. 2, and Four iron biomarkers are used for clinical assessment of iron Supplementary Data 2). For each locus, we report the lead variant status: serum ferritin, serum iron, and total iron-binding capacity (lowest P value) and additional uncorrelated variants (r2 < 0.1) (TIBC) are measured directly, while transferrin saturation within the locus with genome-wide significance. Our criteria for (TSAT) is derived as serum iron divided by TIBC. While serum statistical significance have been previously described9 (see ferritin correlates well with body iron stores in non-inflamed “Methods”). A variant-to-gene mapping algorithm that takes into individuals4, TSAT measures the proportion of iron-binding sites account gene location, variant effect (for coding variants), and of transferrin that are occupied by iron. TSAT indicates the effect on gene expression (eQTL) for each variant (lead variant availability of iron for erythropoiesis and is low in iron deficiency and LD class) was used to choose a single candidate gene for each and high during iron overload. In some forms of anemia (e.g., locus (see “Methods”). Twenty-five of the 62 iron homeostasis- anemia of inflammation) the iron is not transported efficiently to associated sequence variants have a high-confidence predicted the bone marrow for erythropoiesis, despite adequate iron stores. causal gene, 23 variants have multiple top-scoring genes, 36 var- Since in this situation there is adequate ferritin but low TSAT, it is iants have at least one coding variant or eQTL in the LD class, and useful to evaluate TSAT in addition to ferritin4,5. 13 variants have more than one gene with coding variants and/or Genome-wide association studies (GWAS) have previously eQTL in the LD class (Supplementary Data 3). The LD class of a investigated the association between sequence variants and iron variant is defined as all variants having r2 > 0.8 with the variant. homeostasis biomarkers6–8. The largest study to date yielded 11 Linkage disequilibrium (LD) (r2) is estimated based on the Ice- loci: ABO, ARNTL, FADS2, HFE, NAT2, SLC40A1, TEX14, TF, landic population. In cases where variants had more than one top- TFR2, TFRC, and TMPRSS6 associating with one or more iron scoring gene, the gene closest to the lead variant was selected, homeostasis biomarkers (ferritin, iron, TIBC or TSAT)6.To except for two loci where likely candidate genes were present search for additional sequence variants associated with iron among the top-scoring genes (FTL (ferritin light chain) and homeostasis, we performed a GWAS meta-analysis of ferritin, HAMP (hepcidin)) (Supplementary Data 3). Fourteen of the serum iron, TIBC, and TSAT in Iceland and blood donor studies variants associated with more than one biomarker, bringing the from the UK (INTERVAL study) and Denmark (Danish Blood total number of observed associations to 87 (Supplementary Donor Study). This was followed by cross-referencing of iron- Data 2). All our associations have P < 3.0 × 10−8.
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