[en] The N-glycosylation of immunoglobulin G (IgG) affects its structure and function. It has been demonstrated that IgG N-glycosylation patterns are inherited as complex quantitative traits. Genome-wide association studies identified loci harboring genes encoding enzymes directly involved in protein glycosylation as well as loci likely to be involved in regulation of glycosylation biochemical pathways. Many of these loci could be linked to immune functions and risk of inflammatory and autoimmune diseases. The aim of the present study was to discover and replicate new loci associated with IgG N-glycosylation and to investigate possible pleiotropic effects of these loci onto immune function and the risk of inflammatory and autoimmune diseases. We conducted a multivariate genome-wide association analysis of 23 IgG N-glycosylation traits measured in 8090 individuals of European ancestry. The discovery stage was followed up by replication in 3147 people and in silico functional analysis. Our study increased the total number of replicated loci from 22 to 29. For the discovered loci, we suggest a number of genes potentially involved in the control of IgG N-glycosylation. Among the new loci, two (near RNF168 and TNFRSF13B) were previously implicated in rare immune deficiencies and were associated with levels of circulating immunoglobulins. For one new locus (near AP5B1/OVOL1), we demonstrated a potential pleiotropic effect on the risk of asthma. Our findings underline an important link between IgG N-glycosylation and immune function and provide new clues to understanding their interplay.
Disciplines :
Genetics & genetic processes
Author, co-author :
Shadrina, Alexandra S; Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
Zlobin, Alexander ; Université de Liège - ULiège > GIGA > GIGA Medical Genomics - Unit of Animal Genomics ; Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
Zaytseva, Olga O; Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
Klarić, Lucija; Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia ; MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
Sharapov, Sodbo Z; Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
D Pakhomov, Eugene; Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
Perola, Marcus; Genomics and Biomarkers Unit, Department of Health, National Institute for Health and Welfare (THL), Helsinki, Finland
Esko, Tonu; Estonian Genome Center, University of Tartu, Tartu, Estonia
Hayward, Caroline; MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
Wilson, James F; MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK ; Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, Scotland
Lauc, Gordan; Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
Aulchenko, Yurii S; Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia ; PolyOmica, 's-Hertogenbosch 5237 PA, The Netherlands
Tsepilov, Yakov A; Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia ; Laboratory of Theoretical and Applied Functional Genomics, Novosibirsk State University, Novosibirsk 630090, Russia
MRC - Medical Research Council Ministry of Education and Science of the Russian Federation RSF - Russian Science Foundation
Funding text :
Russian Science Foundation (grant number 19-15-00115 to
A.S.Sh., S.Z.S., E.D.P and Y.S.A.); Ministry of Education and
Science of the RF via the Institute of Cytology and Genetics
(project 0259-2021-0009/AAAA-A17-117092070032-4 to A.S.Z.);
Russian Ministry of Science and Education under the 5-100
Excellence Programme (to Y.A.T.); RCUK Innovation Fellowship
from the National Productivity Investment Fund (MR/R026408/1
to L.K.); Croatian National Centre of Research Excellence in
Personalized Healthcare grant (#KK.01.1.1.01.0010 to O.O.Z. and
G.L.), Medical Research Council (UK) Quinquennial programme (to J.F.W.). The Viking Health Study—Shetland (VIKING) was
supported by the MRC Human Genetics Unit quinquennial
programme grant ‘QTL in Health and Disease’. DNA extractions
and genotyping were performed at the Edinburgh Clinical
Research Facility, University of Edinburgh. The CROATIA-Korcula
study was funded by grants from the Medical Research Council
(UK), and Republic of Croatia Ministry of Science, Education and
Sports research grants (108-1080315-0302). The SNP genotyping
for the CROATIA-Korcula2 cohort was performed in the core
genotyping laboratory of the Clinical Research Facility at the
Western General Hospital, Edinburgh, Scotland. The work of C.H.
was supported by an MRC University Unit Programme Grant
MC_UU_00007/10 (QTL in Health and Disease). The color figure
charges were funded by the Russian Science Foundation grant
number 19-15-00115.
Vidarsson, G., Dekkers, G. and Rispens, T. (2014) IgG subclasses and allotypes: from structure to effector functions. Front. Immunol., 5, 520.
Clerc, F., Reiding, K.R., Jansen, B.C., Kammeijer, G.S.M., Bondt, A. and Wuhrer, M. (2016) Human plasma protein N-glycosylation. Glycoconj. J., 33, 309-343.
Ward, E.S. and Ghetie, V. (1995) The effector functions of immunoglobulins: implications for therapy. Ther. Immunol., 2, 77-94.
Gudelj, I., Lauc, G. and Pezer, M. (2018) Immunoglobulin G glycosylation in aging and diseases. Cell. Immunol., 333, 65-79.
Maverakis, E., Kim, K., Shimoda, M., Gershwin, M.E., Patel, F., Wilken, R., Raychaudhuri, S., Ruhaak, L.R. and Lebrilla, C.B. (2015) Glycans in the immune system and the altered glycan theory of autoimmunity: a critical review. J. Autoimmun., 57, 1-13.
Holland, M., Yagi, H., Takahashi, N., Kato, K., Savage, C.O.S., Goodall, D.M. and Jefferis, R. (2006) Differential glycosyla-tion of polyclonal IgG, IgG-Fc and IgG-Fab isolated from the sera of patients with ANCA-associated systemic vasculitis. Biochim. Biophys. Acta, 1760, 669-677.
Arnold, J.N., Wormald, M.R., Sim, R.B., Rudd, P.M. and Dwek, R.A. (2007) The impact of glycosylation on the biological function and structure of human immunoglobulins. Annu. Rev. Immunol., 25, 21-50.
Krištić, J., Vučković, F., Menni, C., Klarić, L., Keser, T., Beceheli, I., Pučić-Baković, M., Novokmet, M., Mangino, M., Thaqi, K. et al. (2014) Glycans are a novel biomarker of chronological and biological ages. J. Gerontol., 69, 779-789.
Lauc, G., Huffman, J.E., Pučić, M., Zgaga, L., Adamczyk, B., Mužinić, A., Novokmet, M., Polašek, O., Gornik, O., Krištić, J. et al. (2013) Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers. PLoS Genet., 9, e1003225.
Shen, X., Klarić, L., Sharapov, S., Mangino, M., Ning, Z., Wu, D., Trbojević-Akmačić, I., Pučić-Baković, M., Rudan, I., Polašek, O. et al. (2017) Multivariate discovery and replication of five novel loci associated with immunoglobulin G N-glycosylation. Nat. Commun., 8, 447.
Wahl, A., van den Akker, E., Klaric, L., Štambuk, J., Benedetti, E., Plomp, R., Razdorov, G., Trbojević-Akmačić, I., Deelen, J., van Heemst, D. et al. (2018) Genome-wide association study on immunoglobulin G glycosylation patterns. Front. Immunol., 9, 277.
Klarić, L., Tsepilov, Y.A., Stanton, C.M., Mangino, M., Sikka, T.T., Esko, T., Pakhomov, E., Salo, P., Deelen, J., McGurnaghan, S.J. et al. (2020) Glycosylation of immunoglobulin G is regulated by a large network of genes pleiotropic with inflammatory diseases. Sci. Adv., 6, eaax0301.
Stein, M.M., Thompson, E.E., Schoettler, N., Helling, B.A., Mag-naye, K.M., Stanhope, C., Igartua, C., Morin, A., Washington, C., Nicolae, D. et al. (2018) A decade of research on the 17q12-21 asthma locus: piecing together the puzzle. J. Allergy Clin. Immunol., 142, 749-764.e3.
Inouye, M., Ripatti, S., Kettunen, J., Lyytikäinen, L.P., Oksala, N., Laurila, P.P., Kangas, A.J., Soininen, P., Savolainen, M.J., Viikari, J. et al. (2012) Novel loci for metabolic networks and multi-tissue expression studies reveal genes for atherosclerosis. PLoS Genet., 8, e1002907.
Stephens, M. (2013) A unified framework for association analysis with multiple related phenotypes. PLoS One, 8, e65245.
Tsepilov, Y.A., Sharapov, S.Z., Zaytseva, O.O., Krumsek, J., Prehn, C., Adamski, J., Kastenmüller, G., Wang-Sattler, R., Strauch, K., Gieger, C. et al. (2018) A network-based conditional genetic association analysis of the human metabolome. Gigascience, 7, giy137.
Kraft, P., Zeggini, E. and Ioannidis, J.P.A. (2009) Replication in genome-wide association studies. Stat. Sci., 24, 561-573.
Pučić, M., Knežević, A., Vidič, J., Adamczyk, B., Novokmet, M., Polašek, O., Gornik, O., Šupraha-Goreta, S., Wormald, M.R., Redžic, I. et al. (2011) High throughput isolation and glycosylation analysis of IgG-variability and heritability of the IgG glycome in three isolated human populations. Mol. Cell. Proteomics, 10, M111.010090.
Russell, A.C., Šimurina, M., Garcia, M.T., Novokmet, M., Wang, Y., Rudan, I., Campbell, H., Lauc, G., Thomas, M.G. and Wang, W. (2017) The N-glycosylation of immunoglobulin G as a novel biomarker of Parkinson's disease. Glycobiology, 27, 501-510.
Varki, A. and Sharon, N. (2009) Historical background and overview. In Varki, A., Cummings, R.D., Esko, J.D., Freeze, H.H., Stanley, P., Bertozzi, C.R., Hart, G.W. and Etzler, M.E. (eds), Essentials of Glycobiology, 2nd ed. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY.
Doherty, M., Theodoratou, E., Walsh, I., Adamczyk, B., Stöckmann, H., Agakov, F., Timofeeva, M., Trbojević-Akmačić, I., Vučković, F., Duffy, F. et al. (2018) Plasma N-glycans in col-orectal cancer risk. Sci. Rep., 8, 8655.
McLaren, W., Gil, L., Hunt, S.E., Riat, H.S., Ritchie, G.R.S., Thormann, A., Flicek, P. and Cunningham, F. (2016) The Ensembl Variant Effect Predictor. Genome Biol., 17, 122.
Machiela, M.J. and Chanock, S.J. (2015) LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics, 31, 3555-3557.
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M.R., Powell, J.E., Montgomery, G.W., Goddard, M.E., Wray, N.R., Visscher, P.M. et al.(2016) Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet., 48, 481-487.
Pers, T.H., Karjalainen, J.M., Chan, Y., Westra, H.-J., Wood, A.R., Yang, J., Lui, J.C., Vedantam, S., Gustafsson, S., Esko, T. et al. (2015) Biological interpretation of genome-wide association studies using predicted gene functions. Nat. Commun., 6, 5890.
Huffman, J.E., Knežević, A., Vitart, V., Kattla, J., Adamczyk, B., Novokmet, M., Igl, W., Pučić, M., Zgaga, L., Johannson, Å. et al. (2011) Polymorphisms in B3GAT1, SLC9A9 and MGAT5 are associated with variation within the human plasma N-glycome of 3533 European adults. Hum. Mol. Genet., 20, 5000-5011.
Sharapov, S.Z., Shadrina, A.S., Tsepilov, Y.A., Elgaeva, E.E., Tiys, E.S., Feoktistova, S.G., Zaytseva, O.O., Vuckovic, F., Cuadrat, R., Jäger, S. et al. (2021) Replication of fifteen loci involved in human plasma protein N-glycosylation in 4, 802 samples from four cohorts. Glycobiology., 31, 82-88.
Roxrud, I., Raiborg, C., Gilfillan, G.D., Strømme, P. and Stenmark, H. (2009) Dual degradation mechanisms ensure disposal of NHE6 mutant protein associated with neurological disease. Exp. Cell Res., 315, 3014-3027.
Von Bülow, G.U. and Bram, R.J. (1997) NF-AT activation induced by a CAML-interacting member of the tumor necrosis factor receptor superfamily. Science, 278, 138-141.
Ozcan, E., Garibyan, L., Lee, J.J.Y., Bram, R.J., Lam, K.P. and Geha, R.S. (2009) Transmembrane activator, calcium modulator, and cyclophilin ligand interactor drives plasma cell differentiation in LPS-activated B cells. J. Allergy Clin. Immunol., 123, 1277-1286.e5.
Castigli, E., Wilson, S.A., Elkhal, A., Ozcan, E., Garibyan, L. and Geha, R.S. (2007) Transmembrane activator and calcium modulator and cyclophilin ligand interactor enhances CD40-driven plasma cell differentiation. J. Allergy Clin. Immunol., 120, 885-891.
Castigli, E., Wilson, S., Garibyan, L., Rachid, R., Bonilla, F., Schneider, L., Morra, M., Curran, J. and Geha, R. (2007) Reex-amining the role of TACI coding variants in common variable immunodeficiency and selective IgA deficiency. Nat. Genet., 39, 430-431.
Janzi, M., Melén, E., Kull, I., Wickman, M. and Hammarström, L. (2012) Rare mutations in TNFRSF13B increase the risk of asthma symptoms in Swedish children. Genes Immun., 13, 59-65.
Liao, M., Ye, F., Zhang, B., Huang, L., Xiao, Q., Qin, M., Mo, L., Tan, A., Gao, Y., Lu, Z. et al. (2012) Genome-wide association study identifies common variants at TNFRSF13B associated with IgG level in a healthy Chinese male population. Genes Immun., 13, 509-513.
Jonsson, S., Sveinbjornsson, G., De Lapuente Portilla, A.L., Swaminathan, B., Plomp, R., Dekkers, G., Ajore, R., Ali, M., Bentlage, A.E.H., Elmér, E. et al. (2017) Identification of sequence variants influencing immunoglobulin levels. Nat. Genet., 49, 1182-1191.
Ramachandran, S., Chahwan, R., Nepal, R.M., Frieder, D., Panier, S., Roa, S., Zaheen, A., Durocher, D., Scharff, M.D. and Martin, A. (2010) The RNF8/RNF168 ubiquitin ligase cascade facilitates class switch recombination. Proc. Natl. Acad. Sci. U. S. A., 107, 809-814.
Stewart, G.S., Panier, S., Townsend, K., Al-Hakim, A.K., Kolas, N.K., Miller, E.S., Nakada, S., Ylanko, J., Olivarius, S., Mendez, M. et al. (2009) The RIDDLE syndrome protein mediates a ubiquitin-dependent signaling cascade at sites of DNA damage. Cell, 136, 420-434.
Marenholz, I., Esparza-Gordillo, J., Rüschendorf, F., Bauerfeind, A., Strachan, D.P., Spycher, B.D., Baurecht, H., Margaritte-Jeannin, P., Sääf, A., Kerkhof, M. et al. (2015) Meta-analysis identifies seven susceptibility loci involved in the atopic march. Nat. Commun., 6, 8804.
Johansson, Å., Rask-Andersen, M., Karlsson, T. and Ek, W.E. (2019) Genome-wide association analysis of 350 000
Caucasians from the UK Biobank identifies novel loci for asthma, hay fever and eczema. Hum. Mol. Genet., 28, 4022-4041.
Paternoster, L., Standl, M., Chen, C.M., Ramasamy, A., Bøpnnelykke, K., Duijts, L., Ferreira, M.A., Alves, A.C., Thyssen, J.P., Albrecht, E. et al. (2012) Meta-analysis of genome-wide association studies identifies three new risk loci for atopic dermatitis. Nat. Genet., 44, 187-192.
Paternoster, L., Standl, M., Waage, J., Baurecht, H., Hotze, M., Strachan, D.P., Curtin, J.A., Bønnelykke, K., Tian, C., Taka-hashi, A. et al. (2015) Multi-ancestry genome-wide association study of 21, 000 cases and 95, 000 controls identifies new risk loci for atopic dermatitis. Nat. Genet., 47, 1449-1456.
Christou, M.A., Ntritsos, G., Markozannes, G., Koskeridis, F., Nikas, S.N., Karasik, D., Kiel, D.P., Evangelou, E. and Ntzani, E.E. (2020) A genome-wide scan for pleiotropy between bone mineral density and nonbone phenotypes. Bone Res., 8, 1-9.
Reese, S.E., Xu, C.J., den Dekker, H.T., Lee, M.K., Sikdar, S., Ruiz-Arenas, C., Merid, S.K., Rezwan, F.I., Page, C.M., Ullemar, V. et al. (2019) Epigenome-wide meta-analysis of DNA methy-lation and childhood asthma. J. Allergy Clin. Immunol., 143, 2062-2074.
Hirst, J., D. Barlow, L., Francisco, G.C., Sahlender, D.A., Seaman, M.N.J., Dacks, J.B. and Robinson, M.S. (2011) The fifth adaptor protein complex. PLoS Biol., 9, e1001170.
Hirst, J., Itzhak, D.N., Antrobus, R., Borner, G.H.H. and Robinson, M.S. (2018) Role of the AP-5 adaptor protein complex in late endosome-to-Golgi retrieval. PLoS Biol., 16, e2004411.
Nair, M., Teng, A., Bilanchone, V., Agrawal, A., Li, B. and Dai, X. (2006) Ovol1 regulates the growth arrest of embryonic epidermal progenitor cells and represses c-myc transcription. J. Cell Biol., 173, 253-264.
Li, B., Nair, M., Mackay, D.R., Bilanchone, V., Hu, M., Fallahi, M., Song, H., Dai, Q., Cohen, P.E. and Dai, X. (2005) Ovol1 regulates meiotic pachytene progression during spermatogenesis by repressing Id2 expression. Development, 132, 1463-1473.
Dai, X., Schonbaum, C., Degenstein, L., Bai, W., Mahowald, A. and Fuchs, E. (1998) The ovo gene required for cuticle formation and oogenesis in flies is involved in hair formation and spermatogenesis in mice. Genes Dev., 12, 3452-3463.
Tsuji, G., Ito, T., Chiba, T., Mitoma, C., Nakahara, T., Uchi, H. and Furue, M. (2018) The role of the OVOL1-OVOL2 axis in normal and diseased human skin. J. Dermatol. Sci., 90, 227-231.
Hucthagowder, V., Sausgruber, N., Kim, K.H., Angle, B., Marmorstein, L.Y. and Urban, Z. (2006) Fibulin-4: a novel gene for an autosomal recessive cutis laxa syndrome. Am. J. Hum. Genet., 78, 1075-1080.
Hoyer, J., Kraus, C., Hammersen, G., Geppert, J.P. and Rauch, A. (2009) Lethal cutis laxa with contractural arachnodactyly, overgrowth and soft tissue bleeding due to a novel homozy-gous fibulin-4 gene mutation. Clin. Genet., 76, 276-281.
Nakayama, T. and Kimura, M.Y. (2010) Memory Th1/Th2 cell generation controlled by Schnurri-2. Adv. Exp. Med. Biol., 684, 1-10.
Staton, T.L., Lazarevic, V., Jones, D.C., Lanser, A.J., Takagi, T., Ishii, S. and Glimcher, L.H. (2011) Dampening of death pathways by schnurri-2 is essential for T-cell development. Nature, 472, 105-110.
Rosnet, O., Blanco-Betancourt, C., Grivel, K., Richter, K. and Schiff, C. (2004) Binding of free immunoglobulin light chains to VpreB3 inhibits their maturation and secretion in chicken B cells. J. Biol. Chem., 279, 10228-10236.
Szabo, S.J., Kim, S.T., Costa, G.L., Zhang, X., Fathman, C.G. and Glimcher, L.H. (2000) A novel transcription factor, T-bet, directs Th1 lineage commitment. Cell, 100, 655-669.
Martincic, K., Alkan, S.A., Cheatle, A., Borghesi, L. and Mil-carek, C. (2009) Transcription elongation factor ELL2 directs immunoglobulin secretion in plasma cells by stimulating altered RNA processing. Nat. Immunol., 10, 1102-1109.
Klarić, L., Tsepilov, Y.A., Aulchenko, Y.S., Lauc, G. and Hay-ward, C. (2019) GWAS summary statistics for UPLC IgG N-glycosylation traits [dataset]. MRC Human Genetics Unit. Institute of Genetics and Molecular Medicine. University of Edinburgh. doi:10.7488/ds/2481.
Kerr, S.M., Klaric, L., Halachev, M., Hayward, C., Boutin, T.S., Meynert, A.M., Semple, C.A., Tuiskula, A.M., Swan, H., Santoyo-Lopez, J. et al. (2019) An actionable KCNH2 long QT syndrome variant detected by sequence and haplo-type analysis in a population research cohort. Sci. Rep., 9, 10964.
Rudan, I., Marušić, A., Janković, S., Rotim, K., Boban, M., Lauc, G., Grković, I., Dogaš, Z., Zemunik, T., Vatavuk, Z. et al. (2009) 10 001 Dalmatians:' Croatia launches its National Biobank. Croat. Med. J., 50, 4-6.
Shashkova, T.I., Gorev, D.D., Pakhomov, E.D., Shadrina, A.S., Sharapov, S.Z., Tsepilov, Y.A., Karssen, L.C. and Aulchenko, Y.S. (2020) The GWAS-MAP platform for aggregation of results of genome-wide association studies and the GWAS-MAP|homo database of 70 billion genetic associations of human traits. Vavilovskii Zhurnal Genet. Selektsii, 24, 876-884.
Devlin, B. and Roeder, K. (1999) Genomic control for association studies. Biometrics, 55, 997-1004.
Ihaka, R. and Gentleman, R. (1996) R: a language for data analysis and graphics. J. Comput. Graph. Stat., 5, 299.
Ning, Z., Tsepilov, Y.A., Sharapov, S.Z., Grishenko, A.K., Feng, X., Shirali, M., Joshi, P.K., Wilson, J.F., Pawitan, Y., Haley, C.S. et al. (2015) Beyond power: multivariate discovery, replication, and interpretation of pleiotropic loci using summary association statistics. bioRxiv. doi: 10.1101/022269.
McDaid, A.F., Joshi, P.K., Porcu, E., Komljenovic, A., Li, H., Sorrentino, V., Litovchenko, M., Bevers, R.P.J., Ruëger, S., Rey-mond, A. et al. (2017) Bayesian association scan reveals loci associated with human lifespan and linked biomarkers. Nat. Commun., 8, 1-11.
Chang, C.C., Chow, C.C., Tellier, L.C., Vattikuti, S., Purcell, S.M. and Lee, J.J. (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience, 4, 7.
Westra, H.-J., Peters, M.J., Esko, T., Yaghootkar, H., Schurmann, C., Kettunen, J., Christiansen, M.W., Fairfax, B.P., Schramm, K., Powell, J.E. et al. (2013) Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet., 45, 1238-1243.
Momozawa, Y., Dmitrieva, J., Théâtre, E., Deffontaine, V., Rah-mouni, S., Charloteaux, B., Crins, F., Docampo, E., Elansary, M., Gori, A.-S. et al. (2018) IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes. Nat. Commun., 9, 2427.
Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M. et al. (2015) UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med., 12, e1001779.
Okada, Y., Wu, D., Trynka, G., Raj, T., Terao, C., Ikari, K., Kochi, Y., Ohmura, K., Suzuki, A., Yoshida, S. et al. (2013) Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature, 506, 376-381.
Cordell, H.J., Han, Y., Mells, G.F., Li, Y., Hirschfield, G.M., Greene, C.S., Xie, G., Juran, B.D., Zhu, D., Qian, D.C. et al. (2015) International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways. Nat. Commun., 6, 8019.
Cortes, A., Hadler, J., Pointon, J.P., Robinson, P.C., Karaderi, T., Leo, P., Cremin, K., Pryce, K., Harris, J., Lee, S. et al. (2013) Identification of multiple risk variants for ankylosing spondylitis through high-density genotyping of immune-related loci. Nat. Genet., 45, 730-738.
Liu, J.Z., Van Sommeren, S., Huang, H., Ng, S.C., Alberts, R., Takahashi, A., Ripke, S., Lee, J.C., Jostins, L., Shah, T. et al. (2015) Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet., 47, 979-986.
Sharapov, S.Z., Tsepilov, Y.A., Klaric, L., Mangino, M., Thareja, G., Shadrina, A.S., Simurina, M., Dagostino, C., Dmitrieva, J., Vilaj, M. et al. (2019) Defining the genetic control of human blood plasma N-glycome using genome-wide association study. Hum. Mol. Genet., 28, 2062-2077.
