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Your search keyword '"Eyjolfsson, Gudmundur I."' showing total 8 results
Start Over Author "Eyjolfsson, Gudmundur I." Topic genome-wide association study
8 results on '"Eyjolfsson, Gudmundur I."'

1. Sequence variants influencing the regulation of serum IgG subclass levels.

Author

Olafsdottir TA, Thorleifsson G, Lopez de Lapuente Portilla A, Jonsson S, Stefansdottir L, Niroula A, Jonasdottir A, Eggertsson HP, Halldorsson GH, Thorlacius GE, Arnthorsson AO, Bjornsdottir US, Asselbergs FW, Bentlage AEH, Eyjolfsson GI, Gudmundsdottir S, Gunnarsdottir K, Halldorsson BV, Holm H, Ludviksson BR, Melsted P, Norddahl GL, Olafsson I, Saevarsdottir S, Sigurdardottir O, Sigurdsson A, Temming R, Önundarson PT, Thorsteinsdottir U, Vidarsson G, Sulem P, Gudbjartsson DF, Jonsdottir I, Nilsson B, and Stefansson K

Subjects
Humans, Adult, Female, Male, Child, Adolescent, Receptors, IgG genetics, Middle Aged, Immunoglobulin Heavy Chains genetics, Immunoglobulin Heavy Chains blood, Alleles, Young Adult, Autoimmune Diseases genetics, Autoimmune Diseases immunology, Autoimmune Diseases blood, Chromosomes, Human, Pair 17 genetics, Genetic Predisposition to Disease, HLA Antigens genetics, HLA Antigens immunology, Membrane Proteins, Immunoglobulin G blood, Immunoglobulin G immunology, Immunoglobulin G genetics, Genome-Wide Association Study, Asthma genetics, Asthma immunology, Asthma blood, Polymorphism, Single Nucleotide
Abstract

Immunoglobulin G (IgG) is the main isotype of antibody in human blood. IgG consists of four subclasses (IgG1 to IgG4), encoded by separate constant region genes within the Ig heavy chain locus (IGH). Here, we report a genome-wide association study on blood IgG subclass levels. Across 4334 adults and 4571 individuals under 18 years, we discover ten new and identify four known variants at five loci influencing IgG subclass levels. These variants also affect the risk of asthma, autoimmune diseases, and blood traits. Seven variants map to the IGH locus, three to the Fcγ receptor (FCGR) locus, and two to the human leukocyte antigen (HLA) region, affecting the levels of all IgG subclasses. The most significant associations are observed between the G1m (f), G2m(n) and G3m(b*) allotypes, and IgG1, IgG2 and IgG3, respectively. Additionally, we describe selective associations with IgG4 at 16p11.2 (ITGAX) and 17q21.1 (IKZF3, ZPBP2, GSDMB, ORMDL3). Interestingly, the latter coincides with a highly pleiotropic signal where the allele associated with lower IgG4 levels protects against childhood asthma but predisposes to inflammatory bowel disease. Our results provide insight into the regulation of antibody-mediated immunity that can potentially be useful in the development of antibody based therapeutics., (© 2024. The Author(s).)

Published
2024
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2. Genome-wide association meta-analysis yields 20 loci associated with gallstone disease.

Author

Ferkingstad E, Oddsson A, Gretarsdottir S, Benonisdottir S, Thorleifsson G, Deaton AM, Jonsson S, Stefansson OA, Norddahl GL, Zink F, Arnadottir GA, Gunnarsson B, Halldorsson GH, Helgadottir A, Jensson BO, Kristjansson RP, Sveinbjornsson G, Sverrisson DA, Masson G, Olafsson I, Eyjolfsson GI, Sigurdardottir O, Holm H, Jonsdottir I, Olafsson S, Steingrimsdottir T, Rafnar T, Bjornsson ES, Thorsteinsdottir U, Gudbjartsson DF, Sulem P, and Stefansson K

Subjects
Gallstones genetics, Hepatocyte Nuclear Factor 4 genetics, Humans, Mutation, Missense genetics, Organic Anion Transporters, Sodium-Dependent genetics, Symporters genetics, alpha 1-Antitrypsin genetics, Gallstones metabolism, Genome-Wide Association Study methods
Abstract

Gallstones are responsible for one of the most common diseases in the Western world and are commonly treated with cholecystectomy. We perform a meta-analysis of two genome-wide association studies of gallstone disease in Iceland and the UK, totaling 27,174 cases and 736,838 controls, uncovering 21 novel gallstone-associated variants at 20 loci. Two distinct low frequency missense variants in SLC10A2, encoding the apical sodium-dependent bile acid transporter (ASBT), associate with an increased risk of gallstone disease (Pro290Ser: OR = 1.36 [1.25-1.49], P = 2.1 × 10 -12 , MAF = 1%; Val98Ile: OR = 1.15 [1.10-1.20], P = 1.8 × 10 -10 , MAF = 4%). We demonstrate that lower bile acid transport by ASBT is accompanied by greater risk of gallstone disease and highlight the role of the intestinal compartment of the enterohepatic circulation of bile acids in gallstone disease susceptibility. Additionally, two low frequency missense variants in SERPINA1 and HNF4A and 17 common variants represent novel associations with gallstone disease.

Published
2018
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3. Genome-wide associations for benign prostatic hyperplasia reveal a genetic correlation with serum levels of PSA.

Author

Gudmundsson J, Sigurdsson JK, Stefansdottir L, Agnarsson BA, Isaksson HJ, Stefansson OA, Gudjonsson SA, Gudbjartsson DF, Masson G, Frigge ML, Stacey SN, Sulem P, Halldorsson GH, Tragante V, Holm H, Eyjolfsson GI, Sigurdardottir O, Olafsson I, Jonsson T, Jonsson E, Barkardottir RB, Hilmarsson R, Asselbergs FW, Geirsson G, Thorsteinsdottir U, Rafnar T, Thorleifsson G, and Stefansson K

Subjects
Acetylation, Aged, Computational Biology, Genetic Predisposition to Disease, Histones metabolism, Humans, Iceland, Lower Urinary Tract Symptoms blood, Lower Urinary Tract Symptoms genetics, Lysine metabolism, Male, Meta-Analysis as Topic, Multifactorial Inheritance genetics, Mutation genetics, Phenotype, Quantitative Trait Loci genetics, Risk Factors, United Kingdom, Genome-Wide Association Study, Prostate-Specific Antigen blood, Prostatic Hyperplasia blood, Prostatic Hyperplasia genetics
Abstract

Benign prostatic hyperplasia and associated lower urinary tract symptoms (BPH/LUTS) are common conditions affecting the majority of elderly males. Here we report the results of a genome-wide association study of symptomatic BPH/LUTS in 20,621 patients and 280,541 controls of European ancestry, from Iceland and the UK. We discovered 23 genome-wide significant variants, located at 14 loci. There is little or no overlap between the BPH/LUTS variants and published prostate cancer risk variants. However, 15 of the variants reported here also associate with serum levels of prostate specific antigen (PSA) (at a Bonferroni corrected P < 0.0022). Furthermore, there is a strong genetic correlation, r g  = 0.77 (P = 2.6 × 10 -11 ), between PSA and BPH/LUTS, and one standard deviation increase in a polygenic risk score (PRS) for BPH/LUTS increases PSA levels by 12.9% (P = 1.6×10 -55 ). These results shed a light on the genetic background of BPH/LUTS and its substantial influence on PSA levels.

Published
2018
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4. A genome-wide association study yields five novel thyroid cancer risk loci.

Author

Gudmundsson J, Thorleifsson G, Sigurdsson JK, Stefansdottir L, Jonasson JG, Gudjonsson SA, Gudbjartsson DF, Masson G, Johannsdottir H, Halldorsson GH, Stacey SN, Helgason H, Sulem P, Senter L, He H, Liyanarachchi S, Ringel MD, Aguillo E, Panadero A, Prats E, Garcia-Castaño A, De Juan A, Rivera F, Xu L, Kiemeney LA, Eyjolfsson GI, Sigurdardottir O, Olafsson I, Kristvinsson H, Netea-Maier RT, Jonsson T, Mayordomo JI, Plantinga TS, Hjartarson H, Hrafnkelsson J, Sturgis EM, Thorsteinsdottir U, Rafnar T, de la Chapelle A, and Stefansson K

Subjects
Adult, Asian People genetics, Case-Control Studies, Chromosomes, Human genetics, Female, Gene Expression Regulation, Neoplastic, Gene Frequency genetics, Genetic Predisposition to Disease, Genomic Structural Variation, Genotype, Humans, Male, Middle Aged, Pituitary Hormones analysis, Risk Factors, Thyroid Cancer, Papillary, Thyroid Gland metabolism, Thyroid Neoplasms metabolism, White People genetics, Whole Genome Sequencing, Carcinoma, Papillary genetics, Genetic Loci, Genome-Wide Association Study, Thyroid Neoplasms genetics
Abstract

The great majority of thyroid cancers are of the non-medullary type. Here we report findings from a genome-wide association study of non-medullary thyroid cancer, including in total 3,001 patients and 287,550 controls from five study groups of European descent. Our results yield five novel loci (all with P combined <3 × 10 -8 ): 1q42.2 (rs12129938 in PCNXL2), 3q26.2 (rs6793295 a missense mutation in LRCC34 near TERC), 5q22.1 (rs73227498 between NREP and EPB41L4A), 10q24.33 (rs7902587 near OBFC1), and two independently associated variants at 15q22.33 (rs2289261 and rs56062135; both in SMAD3). We also confirm recently published association results from a Chinese study of a variant on 5p15.33 (rs2736100 near the TERT gene) and present a stronger association result for a moderately correlated variant (rs10069690; OR=1.20, P=3.2 × 10 -7 ) based on our study of individuals of European ancestry. In combination, these results raise several opportunities for future studies of the pathogenesis of thyroid cancer.

Published
2017
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5. Genetic architecture of vitamin B12 and folate levels uncovered applying deeply sequenced large datasets.

Author

Grarup N, Sulem P, Sandholt CH, Thorleifsson G, Ahluwalia TS, Steinthorsdottir V, Bjarnason H, Gudbjartsson DF, Magnusson OT, Sparsø T, Albrechtsen A, Kong A, Masson G, Tian G, Cao H, Nie C, Kristiansen K, Husemoen LL, Thuesen B, Li Y, Nielsen R, Linneberg A, Olafsson I, Eyjolfsson GI, Jørgensen T, Wang J, Hansen T, Thorsteinsdottir U, Stefánsson K, and Pedersen O

Subjects
Alzheimer Disease genetics, Alzheimer Disease metabolism, Denmark, Exome, Folic Acid metabolism, Folic Acid Deficiency metabolism, Genome, Human, Humans, Iceland, Methylenetetrahydrofolate Reductase (NADPH2) genetics, Vitamin B 12 metabolism, Folic Acid blood, Folic Acid Deficiency genetics, Genome-Wide Association Study, Quantitative Trait Loci, Vitamin B 12 blood
Abstract

Genome-wide association studies have mainly relied on common HapMap sequence variations. Recently, sequencing approaches have allowed analysis of low frequency and rare variants in conjunction with common variants, thereby improving the search for functional variants and thus the understanding of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B(12) (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined samples of 45,576 and 37,341 individuals with serum B(12) and folate measurements, respectively. We found six novel loci associating with serum B(12) (CD320, TCN2, ABCD4, MMAA, MMACHC) or folate levels (FOLR3) and confirmed seven loci for these traits (TCN1, FUT6, FUT2, CUBN, CLYBL, MUT, MTHFR). Conditional analyses established that four loci contain additional independent signals. Interestingly, 13 of the 18 identified variants were coding and 11 of the 13 target genes have known functions related to B(12) and folate pathways. Contrary to epidemiological studies we did not find consistent association of the variants with cardiovascular diseases, cancers or Alzheimer's disease although some variants demonstrated pleiotropic effects. Although to some degree impeded by low statistical power for some of these conditions, these data suggest that sequence variants that contribute to the population diversity in serum B(12) or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations., Competing Interests: I have read the journal's policy and declare that the authors from deCODE Genetics (P. Sulem, G. Thorleifsson, V. Steinthorsdottir, H. Bjarnason, D. F. Gudbjartsson, O. T. Magnusson, A. Kong, G. Masson, U. Thorsteinsdottir, and K. Stefánsson) are employees of deCODE Genetics or own stock options in deCODE Genetics. The remaining authors have declared that no competing interests exist.

Published
2013
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6. Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma.

Author

Chambers JC, Zhang W, Sehmi J, Li X, Wass MN, Van der Harst P, Holm H, Sanna S, Kavousi M, Baumeister SE, Coin LJ, Deng G, Gieger C, Heard-Costa NL, Hottenga JJ, Kühnel B, Kumar V, Lagou V, Liang L, Luan J, Vidal PM, Mateo Leach I, O'Reilly PF, Peden JF, Rahmioglu N, Soininen P, Speliotes EK, Yuan X, Thorleifsson G, Alizadeh BZ, Atwood LD, Borecki IB, Brown MJ, Charoen P, Cucca F, Das D, de Geus EJ, Dixon AL, Döring A, Ehret G, Eyjolfsson GI, Farrall M, Forouhi NG, Friedrich N, Goessling W, Gudbjartsson DF, Harris TB, Hartikainen AL, Heath S, Hirschfield GM, Hofman A, Homuth G, Hyppönen E, Janssen HL, Johnson T, Kangas AJ, Kema IP, Kühn JP, Lai S, Lathrop M, Lerch MM, Li Y, Liang TJ, Lin JP, Loos RJ, Martin NG, Moffatt MF, Montgomery GW, Munroe PB, Musunuru K, Nakamura Y, O'Donnell CJ, Olafsson I, Penninx BW, Pouta A, Prins BP, Prokopenko I, Puls R, Ruokonen A, Savolainen MJ, Schlessinger D, Schouten JN, Seedorf U, Sen-Chowdhry S, Siminovitch KA, Smit JH, Spector TD, Tan W, Teslovich TM, Tukiainen T, Uitterlinden AG, Van der Klauw MM, Vasan RS, Wallace C, Wallaschofski H, Wichmann HE, Willemsen G, Würtz P, Xu C, Yerges-Armstrong LM, Abecasis GR, Ahmadi KR, Boomsma DI, Caulfield M, Cookson WO, van Duijn CM, Froguel P, Matsuda K, McCarthy MI, Meisinger C, Mooser V, Pietiläinen KH, Schumann G, Snieder H, Sternberg MJ, Stolk RP, Thomas HC, Thorsteinsdottir U, Uda M, Waeber G, Wareham NJ, Waterworth DM, Watkins H, Whitfield JB, Witteman JC, Wolffenbuttel BH, Fox CS, Ala-Korpela M, Stefansson K, Vollenweider P, Völzke H, Schadt EE, Scott J, Järvelin MR, Elliott P, and Kooner JS

Subjects
Delta-5 Fatty Acid Desaturase, Enzymes genetics, Humans, Polymorphism, Single Nucleotide, Enzymes blood, Genome-Wide Association Study, Liver enzymology
Abstract

Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.

Published
2011
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7. Association of variants at UMOD with chronic kidney disease and kidney stones-role of age and comorbid diseases.

Author

Gudbjartsson DF, Holm H, Indridason OS, Thorleifsson G, Edvardsson V, Sulem P, de Vegt F, d'Ancona FC, den Heijer M, Wetzels JF, Franzson L, Rafnar T, Kristjansson K, Bjornsdottir US, Eyjolfsson GI, Kiemeney LA, Kong A, Palsson R, Thorsteinsdottir U, and Stefansson K

Subjects
Age Factors, Case-Control Studies, Comorbidity, Creatinine blood, Gout, Humans, Iceland, Netherlands, Polymorphism, Single Nucleotide, Risk Factors, Urea blood, Uric Acid blood, Genetic Variation, Genome-Wide Association Study, Kidney Calculi genetics, Renal Insufficiency, Chronic genetics, Uromodulin genetics
Abstract

Chronic kidney disease (CKD) is a worldwide public health problem that is associated with substantial morbidity and mortality. To search for sequence variants that associate with CKD, we conducted a genome-wide association study (GWAS) that included a total of 3,203 Icelandic cases and 38,782 controls. We observed an association between CKD and a variant with 80% population frequency, rs4293393-T, positioned next to the UMOD gene (GeneID: 7369) on chromosome 16p12 (OR = 1.25, P = 4.1x10(-10)). This gene encodes uromodulin (Tamm-Horsfall protein), the most abundant protein in mammalian urine. The variant also associates significantly with serum creatinine concentration (SCr) in Icelandic subjects (N = 24,635, P = 1.3 x 10(-23)) but not in a smaller set of healthy Dutch controls (N = 1,819, P = 0.39). Our findings validate the association between the UMOD variant and both CKD and SCr recently discovered in a large GWAS. In the Icelandic dataset, we demonstrate that the effect on SCr increases substantially with both age (P = 3.0 x 10(-17)) and number of comorbid diseases (P = 0.008). The association with CKD is also stronger in the older age groups. These results suggest that the UMOD variant may influence the adaptation of the kidney to age-related risk factors of kidney disease such as hypertension and diabetes. The variant also associates with serum urea (P = 1.0 x 10(-6)), uric acid (P = 0.0064), and suggestively with gout. In contrast to CKD, the UMOD variant confers protection against kidney stones when studied in 3,617 Icelandic and Dutch kidney stone cases and 43,201 controls (OR = 0.88, P = 5.7 x 10(-5))., Competing Interests: The authors from deCODE own stocks and stock options in the company.

Published
2010
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8. Maps of open chromatin highlight cell type-restricted patterns of regulatory sequence variation at hematological trait loci

Author

Paul, Ds, Albers, Ca, Rendon, A, Voss, K, Stephens, J, Akkerman, Jan Willem N., Albers, Cornelis A., Ale, Algra, Abtehale Al Hussani, Hooman, Allayee, Franco, Anni, Asselbergs, Folkert W., Antony, Attwood, Beverley, Balkau, Stefania, Bandinelli, François, Bastardot, Saonli, Basu, Baumeister, Sebastian E., Jacques, Beckmann, Beben, Benyamin, Ginevra, Biino, Bis, Joshua C., Lorenzo, Bomba, Amélie, Bonnefond, Boomsma, Dorret I., Bradley, John R., François, Cambien, Chambers, John C., Marina, Ciullo, Cookson, William O., Francesco, Cucca, Ana, Cvejic, D'Adamo, ADAMO PIO, John, Danesh, Fabrice, Danjou, Debashish, Das, Gail, Davies, Paul IW de Bakker, de Boer, Rudolf A., Eco JC de Geus, Deary, Ian J., Dedoussis, George V., Panos, Deloukas, Maria, Dimitriou, Christian, Dina, Angela, Döring, Ulrich, Elling, David, Ellinghaus, Paul, Elliott, Gunnar, Engström, Jeanette, Erdmann, Tõnu, Esko, Evans, David M., Eyjolfsson, Gudmundur I., Mario, Falchi, Wei, Feng, Ferreira, Manuel A., Luigi, Ferrucci, Krista, Fischer, Folsom, Aaron R., Paolo, Fortina, Andre, Franke, Lude, Franke, Frazer, Ian H., Philippe, Froguel, Renzo, Galanello, Ganesh, Santhi K., Garner, Stephen F., Gasparini, Paolo, Bernd, Genser, Gibson, Quince D., Christian, Gieger, Girotto, Giorgia, Glazer, Nicole L., Martin, Gögele, Goodall, Alison H., Andreas, Greinacher, Gudbjartsson, Daniel F., Chris, Hammond, Harris, Sarah E., Jaana, Hartiala, Anna Liisa Hartikainen, Hazen, Stanley L., Heckbert, Susan R., Hedblad, Bo, Christian, Hengstenberg, Micha, Hersch, Hicks, Andrew A., Hilma, Holm, Jouke Jan Hottenga, Thomas, Illig, Marjo Riitta Jarvelin, Jennifer, Jolley, Steve, Jupe, Mika, Kähönen, Naoyuki, Kamatani, Stavroula, Kanoni, Kema, Ido P., Kemp, John P., Jyoti, Khadake, Kay Tee Khaw, Kleber, Marcus E., Kooner, Jaspal S., Peter, Kovacs, Brigitte, Kühnel, Marie Christine Kyrtsonis, Yann, Labrune, Vasiliki, Lagou, Claudia, Langenberg, Terho, Lehtimäki, Xinzhong, Li, Liming, Liang, Lifelines Cohort Study, Heather Lloyd Jones, Ruth JF Loos, Lopez, Lorna M., Thomas, Lumley, Leo Pekka Lyytikäinen, Winfried, Maerz, Reedik, Mägi, Massimo, Mangino, Martin, Nicholas G., Andrea, Maschio, Irene Mateo Leach, Barbara, Mcknight, Stuart, Meacham, Medland, Sarah E., Christa, Meisinger, Olle, Melander, Yasin, Memari, Andres, Metspalu, Kathy, Miller, Mitchell, Braxton D., Moffatt, Miriam F., Montgomery, Grant W., Carmel, Moore, Federico, Murgia, Yusuke, Nakamura, Matthias, Nauck, Gerjan, Navis, Nolte, Ilja M., Ute, Nöthlings, Teresa, Nutile, Yukinori, Okada, Isleifur, Olafsson, Onundarson, Pall T., O’Reilly, Paul F., Ouwehand, Willem H., Debora, Parracciani, Afshin, Parsa, Paul, Dirk S., Penninger, Josef M., Penninx, Brenda W., Mario, Pirastu, Pirastu, Nicola, Giorgio, Pistis, Eleonora, Porcu, Laura, Portas, David, Porteous, Anneli, Pouta, Pramstaller, Peter P., Inga, Prokopenko, Psaty, Bruce M., Janne, Pullat, Aparna, Radhakrishnan, Olli, Raitakari, Ramiro Ramirez Solis, Augusto, Rendon, Ried, Janina S., Ring, Susan M., Robino, Antonietta, Rotter, Jerome I., Daniela, Ruggiero, Aimo, Ruokonen, Cinzia, Sala, Andres, Saluments, Samani, Nilesh J., Jennifer, Sambrook, Serena, Sanna, David, Schlessinger, Schmidt, Carsten O., Stefan, Schreiber, Heribert, Schunkert, James, Scott, Joban, Sehmi, Jovana Serbanovic Canic, So Youn Shin, Shuldiner, Alan R., Rob, Sladek, Smit, Johannes H., George Davey Smith, Gustav Smith, J., Smith, Nicholas L., Harold, Snieder, Nicole, Soranzo, Rossella, Sorice, Spector, Timothy D., Starr, John M., Kari, Stefansson, Derek, Stemple, Jonathan, Stephens, Michael, Stumvoll, Patrick, Sulem, Atsushi, Takahashi, Sian Tsung Tan, Toshiko, Tanaka, Clara, Tang, Weihong, Tang, WH Wilson Tang, Kent, Taylor, Albert, Tenesa, Alexander, Teumer, Swee Lay Thein, Unnur, Thorsteinsdottir, Daniela, Toniolo, Anke, Tönjes, Traglia, Michela, Manuela, Uda, Sheila, Ulivi, Pim van der Harst, Ellen van der Schoot, C., van Gilst, Wiek H., Joost van Pelt, L., van Veldhuisen, Dirk J., Niek, Verweij, Visscher, Peter M., Uwe, Völker, Peter, Vollenweider, Katrin, Voss, Wareham, Nicholas J., Lorenz, Wernisch, Harm Jan Westra, Whitfield, John B., Herich, Wichmann, Wiggins, Kerri L., Gonneke, Willemsen, Winkelmann, Bernhard R., Gerald, Wirnsberger, Bruce HR Wolffenbuttel, Jian, Yang, Tsun Po Yang, Weihua, Zhang, Jing Hua Zhao, Paavo, Zitting, Jaap Jan Zwaginga, van der Harst, P, Chambers, Jc, Soranzo, N, Ouwehand, Wh, Deloukas, P., Paul, D, Albers, Ca, Rendon, A, Voss, K, Stephens, J, Jan Willem N., Akkerman, Cornelis A., Alber, Ale, Algra, Abtehale Al, Hussani, Hooman, Allayee, Franco, Anni, Folkert W., Asselberg, Antony, Attwood, Beverley, Balkau, Stefania, Bandinelli, François, Bastardot, Saonli, Basu, Sebastian E., Baumeister, Jacques, Beckmann, Beben, Benyamin, Ginevra, Biino, Joshua C., Bi, Lorenzo, Bomba, Amélie, Bonnefond, Dorret I., Boomsma, John R., Bradley, François, Cambien, John C., Chamber, Marina, Ciullo, William O., Cookson, Francesco, Cucca, Ana, Cvejic, D'Adamo, ADAMO PIO, John, Danesh, Fabrice, Danjou, Debashish, Da, Gail, Davie, Paul IW de, Bakker, Rudolf A., de Boer, Eco JC de, Geu, Ian J., Deary, George V., Dedoussi, Panos, Delouka, Maria, Dimitriou, Christian, Dina, Angela, Döring, Ulrich, Elling, David, Ellinghau, Paul, Elliott, Gunnar, Engström, Jeanette, Erdmann, Tõnu, Esko, David M., Evan, Gudmundur I., Eyjolfsson, Mario, Falchi, Wei, Feng, Manuel A., Ferreira, Luigi, Ferrucci, Krista, Fischer, Aaron R., Folsom, Paolo, Fortina, Andre, Franke, Lude, Franke, Ian H., Frazer, Philippe, Froguel, Renzo, Galanello, Santhi K., Ganesh, Stephen F., Garner, Gasparini, Paolo, Bernd, Genser, Quince D., Gibson, Christian, Gieger, Girotto, Giorgia, Nicole L., Glazer, Martin, Gögele, Alison H., Goodall, Andreas, Greinacher, Daniel F., Gudbjartsson, Chris, Hammond, Sarah E., Harri, Jaana, Hartiala, Anna Liisa, Hartikainen, Stanley L., Hazen, Susan R., Heckbert, Bo, Hedblad, Christian, Hengstenberg, Micha, Hersch, Andrew A., Hick, Hilma, Holm, Jouke Jan, Hottenga, Thomas, Illig, Marjo Riitta, Jarvelin, Jennifer, Jolley, Steve, Jupe, Mika, Kähönen, Naoyuki, Kamatani, Stavroula, Kanoni, Ido P., Kema, John P., Kemp, Jyoti, Khadake, Kay Tee, Khaw, Marcus E., Kleber, Jaspal S., Kooner, Peter, Kovac, Brigitte, Kühnel, Marie Christine, Kyrtsoni, Yann, Labrune, Vasiliki, Lagou, Claudia, Langenberg, Terho, Lehtimäki, Xinzhong, Li, Liming, Liang, Lifelines Cohort, Study, Heather Lloyd, Jone, Ruth JF, Loo, Lorna M., Lopez, Thomas, Lumley, Leo Pekka, Lyytikäinen, Winfried, Maerz, Reedik, Mägi, Massimo, Mangino, Nicholas G., Martin, Andrea, Maschio, Irene Mateo, Leach, Barbara, Mcknight, Stuart, Meacham, Sarah E., Medland, Christa, Meisinger, Olle, Melander, Yasin, Memari, Andres, Metspalu, Kathy, Miller, Braxton D., Mitchell, Miriam F., Moffatt, Grant W., Montgomery, Carmel, Moore, Federico, Murgia, Yusuke, Nakamura, Matthias, Nauck, Gerjan, Navi, Ilja M., Nolte, Ute, Nöthling, Teresa, Nutile, Yukinori, Okada, Isleifur, Olafsson, Pall T., Onundarson, Paul F., O’Reilly, Willem H., Ouwehand, Debora, Parracciani, Afshin, Parsa, Dirk S., Paul, Josef M., Penninger, Brenda W., Penninx, Mario, Pirastu, Pirastu, Nicola, Giorgio, Pisti, Eleonora, Porcu, Laura, Porta, David, Porteou, Anneli, Pouta, Peter P., Pramstaller, Inga, Prokopenko, Bruce M., Psaty, Janne, Pullat, Aparna, Radhakrishnan, Olli, Raitakari, Ramiro Ramirez, Soli, Augusto, Rendon, Janina S., Ried, Susan M., Ring, Robino, Antonietta, Jerome I., Rotter, Daniela, Ruggiero, Aimo, Ruokonen, Cinzia, Sala, Andres, Salument, Nilesh J., Samani, Jennifer, Sambrook, Serena, Sanna, David, Schlessinger, Carsten O., Schmidt, Stefan, Schreiber, Heribert, Schunkert, James, Scott, Joban, Sehmi, Jovana Serbanovic, Canic, So Youn, Shin, Alan R., Shuldiner, Rob, Sladek, Johannes H., Smit, George Davey, Smith, J., Gustav Smith, Nicholas L., Smith, Harold, Snieder, Nicole, Soranzo, Rossella, Sorice, Timothy D., Spector, John M., Starr, Kari, Stefansson, Derek, Stemple, Jonathan, Stephen, Michael, Stumvoll, Patrick, Sulem, Atsushi, Takahashi, Sian Tsung, Tan, Toshiko, Tanaka, Clara, Tang, Weihong, Tang, WH Wilson, Tang, Kent, Taylor, Albert, Tenesa, Alexander, Teumer, Swee Lay, Thein, Unnur, Thorsteinsdottir, Daniela, Toniolo, Anke, Tönje, Traglia, Michela, Manuela, Uda, Sheila, Ulivi, Pim van der, Harst, C., Ellen van der Schoot, Wiek H., van Gilst, L., Joost van Pelt, Dirk J., van Veldhuisen, Niek, Verweij, Peter M., Visscher, Uwe, Völker, Peter, Vollenweider, Katrin, Vo, Nicholas J., Wareham, Lorenz, Wernisch, Harm Jan, Westra, John B., Whitfield, Herich, Wichmann, Kerri L., Wiggin, Gonneke, Willemsen, Bernhard R., Winkelmann, Gerald, Wirnsberger, Bruce HR, Wolffenbuttel, Jian, Yang, Tsun Po, Yang, Weihua, Zhang, Jing Hua, Zhao, Paavo, Zitting, Jaap Jan, Zwaginga, van der Harst, P, Chambers, Jc, Soranzo, N, Ouwehand, Wh, Deloukas, P., Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, EMGO+ - Mental Health, Neuroscience Campus Amsterdam - Brain Imaging Technology, Neuroscience Campus Amsterdam - Brain Mechanisms in Health & Disease, Wellcome Trust Sanger Inst, Cambridge CB10 1SA, England, UCL, UCL Canc Inst, London WC1E 6BT, England, Univ Cambridge, Dept Haematol, Cambridge CB2 0PT, England, Natl Hlth Serv NHS Blood & Transplant, Cambridge CB2 0PT, England, Radboud Univ Nijmegen, Med Ctr, Dept Human Genet, NL-6500 HB Nijmegen, Netherlands, Inst Publ Hlth, MRC Biostat Unit, Cambridge CB2 0SR, England, NIHR Biomed Res Ctr, Cambridge CB2 0PT, England, Univ Groningen, Univ Med Ctr Groningen, Dept Cardiol, NL-9713 GZ Groningen, Netherlands, Univ Groningen, Univ Med Ctr Groningen, Dept Genet, NL-9713 GZ Groningen, Netherlands, Univ London Imperial Coll Sci Technol & Med, Dept Epidemiol & Biostat, London W2 1NY, England, Hammersmith Hosp, Imperial Coll Healthcare NHS Trust, London W12 0HS, England, Royal Brompton & Harefield Hosp NHS Trust, London SW3 6NP, England, Ealing Hosp NHS Trust, Southall UB1 3HW, Middx, England, Psychiatry, Epidemiology and Data Science, NCA - Brain mechanisms in health and disease, NCA - Neurobiology of mental health, EMGO - Mental health, NCA - Brain imaging technology, and Cardiovascular Centre (CVC)

Subjects
Netherlands Twin Register (NTR), Erythrocytes, Genome-wide association study, UNCERTAINTY, Regulatory Sequences, Nucleic Acid, VARIANTS, ANNOTATION, COLORECTAL-CANCER, Histones, 0302 clinical medicine, BINDING, Cluster Analysis, Myeloid Cells, Genetics (clinical), Genetics, hematological trait, 0303 health sciences, Chromosome Mapping, MRP4 ABCC4, Chromatin, Nucleosomes, Phenotype, Organ Specificity, 030220 oncology & carcinogenesis, Blood Platelets, Quantitative Trait Loci, Biology, Quantitative trait locus, Polymorphism, Single Nucleotide, DYNAMIN 3, 03 medical and health sciences, Quantitative Trait, Heritable, MEGAKARYOCYTES, Humans, Cell Lineage, ddc:610, GENOME-WIDE ASSOCIATION, Enhancer, Transcription factor, Gene, ChIA-PET, 030304 developmental biology, Research, Genetic Variation, DNA, Chromatin Assembly and Disassembly, Genetic architecture, Gene Expression Regulation, Genome-Wide Association Study
Abstract

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. Nearly three-quarters of the 143 genetic signals associated with platelet and erythrocyte phenotypes identified by meta-analyses of genome-wide association (GWA) studies are located at non-protein-coding regions. Here, we assessed the role of candidate regulatory variants associated with cell type-restricted, closely related hematological quantitative traits in biologically relevant hematopoietic cell types. We used formaldehyde-assisted isolation of regulatory elements followed by next-generation sequencing (FAIRE-seq) to map regions of open chromatin in three primary human blood cells of the myeloid lineage. In the precursors of platelets and erythrocytes, as well as in monocytes, we found that open chromatin signatures reflect the corresponding hematopoietic lineages of the studied cell types and associate with the cell type-specific gene expression patterns. Dependent on their signal strength, open chromatin regions showed correlation with promoter and enhancer histone marks, distance to the transcription start site, and ontology classes of nearby genes. Cell type-restricted regions of open chromatin were enriched in sequence variants associated with hematological indices. The majority (63.6%) of such candidate functional variants at platelet quantitative trait loci (QTLs) coincided with binding sites of five transcription factors key in regulating megakaryopoiesis. We experimentally tested 13 candidate regulatory variants at 10 platelet QTLs and found that 10 (76.9%) affected protein binding, suggesting that this is a frequent mechanism by which regulatory variants influence quantitative trait levels. Our findings demonstrate that combining large-scale GWA data with open chromatin profiles of relevant cell types can be a powerful means of dissecting the genetic architecture of closely related quantitative traits. Marie-Curie Initial Training Network NETSIM British Heart Foundation RG/09/12/28096 National Institutes for Health RP-PG-0310-1002 Wellcome Trust 098051 info:eu-repo/grantAgreement/EC/FP7/282510

Published
2013
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