👤 Nilufer Rahmioglu

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Nina Shigesi, Holly R Harris, Hai Fang +11 more · 2025 · Human reproduction (Oxford, England) · Oxford University Press · added 2026-04-24
Is there an increased risk of immunological diseases among endometriosis patients, and does a shared genetic basis contribute to this risk? Endometriosis patients show a significantly increased risk o Show more
Is there an increased risk of immunological diseases among endometriosis patients, and does a shared genetic basis contribute to this risk? Endometriosis patients show a significantly increased risk of autoimmune, autoinflammatory, and mixed-pattern diseases, including rheumatoid arthritis, multiple sclerosis, coeliac disease, osteoarthritis, and psoriasis, with genetic correlations between endometriosis and osteoarthritis, rheumatoid arthritis, and multiple sclerosis, and a potential causal link to rheumatoid arthritis. The epidemiological evidence for an increased risk of immunological diseases among women with endometriosis is limited in scope and has varied in robustness due to the opportunity for biases. The presence of a biological basis for increased comorbidity across immunological conditions has not been investigated. Here we investigate the phenotypic and genetic association between endometriosis and 31 immune conditions in the UK Biobank. Phenotypic analyses between endometriosis and immune conditions (17 classical autoimmune, 10 autoinflammatory, and 4 mixed-pattern diseases) were conducted using two approaches (8223 endometriosis, 64 620 immunological disease cases): (i) retrospective cohort study design to incorporate temporality between diagnoses and (ii) cross-sectional analysis for simple association. Genome-wide association studies (GWAS) and meta-analyses for those immune conditions that showed phenotypic association with endometriosis (1493-77 052 cases) were conducted. Comprehensive phenotypic association analyses were conducted in females in the UK Biobank. GWAS for immunological conditions were conducted in females-only and sex-combined study populations in UK Biobank and meta-analysed with existing largest available GWAS results. Genetic correlation and Mendelian randomization (MR) analyses were conducted to investigate potential causal relationships. Those immune conditions with significant genetic correlation with endometriosis were included in multi-trait analysis of GWAS to boost discovery of novel and shared genetic variants. These shared variants were functionally annotated to identify affected genes utilizing expression quantitative trait loci (eQTL) data from GTEx and eQTLGen databases. Biological pathway enrichment analysis was conducted to identify shared underlying biological pathways. In both retrospective cohort and cross-sectional analyses, endometriosis patients were at significantly increased (30-80%) risk of classical autoimmune (rheumatoid arthritis, multiple sclerosis, coeliac disease), autoinflammatory (osteoarthritis), and mixed-pattern (psoriasis) diseases. Osteoarthritis (genetic correlation (rg) = 0.28, P = 3.25 × 10-15), rheumatoid arthritis (rg = 0.27, P = 1.5 × 10-5) and multiple sclerosis (rg = 0.09, P = 4.00 × 10-3) were significantly genetically correlated with endometriosis. MR analysis suggested a causal association between endometriosis and rheumatoid arthritis (OR = 1.16, 95% CI = 1.02-1.33). eQTL analyses highlighted genes affected by shared risk variants, enriched for seven pathways across all four conditions, with three genetic loci shared between endometriosis and osteoarthritis (BMPR2/2q33.1, BSN/3p21.31, MLLT10/10p12.31) and one with rheumatoid arthritis (XKR6/8p23.1). We conducted the first female-specific GWAS analyses for immune conditions. Given the novelty of these analyses, the sample sizes from which results were derived were limited compared to sex-combined GWAS meta-analyses, which limited the power to use female-specific summary statistics to uncover the shared genetic basis with endometriosis in follow-up analyses. Secondly, the 39 genome-wide significant endometriosis-associated variants used as instrumental variables in the MR analysis explained approximately 5% of disease variation, which may account for the nominal or non-significant MR results. Endometriosis patients have a moderately increased risk for osteoarthritis, rheumatoid arthritis, and to a lesser extent, multiple sclerosis, due to underlying shared biological mechanisms. Clinical implications primarily involve the need for increased awareness and vigilance. The shared genetic basis opens up opportunities for developing new treatments or repurposing therapies across these conditions. We thank all the UK Biobank and 23andMe participants. Part of this research was conducted using the UK Biobank Resource under Application Number 9637. N.R. was supported by a grant from the Wellbeing of Women UK (RG2031) and the EU Horizon 2020 funded project FEMaLe (101017562). A.P.M. was supported in part by Versus Arthritis (grant 21754). H.F. was supported by the National Natural Science Foundation of China (grant 32170663). N.R., S.A.M., and K.T.Z. were supported in part by a grant from CDMRP DoD PRMRP (W81XWH-20-PRMRP-IIRA). K.T.Z. and C.M.B. reported grants in 3 years prior, outside the submitted work, from Bayer AG, AbbVie Inc., Volition Rx, MDNA Life Sciences, PrecisionLife Ltd., and Roche Diagnostics Inc. S.A.M. reports grants in the 3 years prior, outside this submitted work, from AbbVie Inc. N.R. is a consultant for Endogene.bio, outside this submitted work. The other authors have no conflicts of interest to declare. N/A. Show less
đź“„ PDF DOI: 10.1093/humrep/deaf062
MLLT10
Nilufer Rahmioglu, Sally Mortlock, Marzieh Ghiasi +135 more · 2023 · Nature genetics · Nature · added 2026-04-24
Nilufer Rahmioglu, Sally Mortlock, Marzieh Ghiasi, Peter L Møller, Lilja Stefansdottir, Geneviève Galarneau, Constance Turman, Rebecca Danning, Matthew H Law, Yadav Sapkota, Paraskevi Christofidou, Sini Skarp, Ayush Giri, Karina Banasik, Michal Krassowski, Maarja Lepamets, Błażej Marciniak, Margit Nõukas, Danielle Perro, Eeva Sliz, Marta Sobalska-Kwapis, Gudmar Thorleifsson, Nura F Topbas-Selcuki, Allison Vitonis, David Westergaard, Ragnheidur Arnadottir, Kristoffer S Burgdorf, Archie Campbell, Cecilia S K Cheuk, Caterina Clementi, James Cook, Immaculata De Vivo, Amy DiVasta, O Dorien, Jacqueline F Donoghue, Todd Edwards, Pierre Fontanillas, Jenny N Fung, Reynir T Geirsson, Jane E Girling, Paivi Harkki, Holly R Harris, Martin Healey, Oskari Heikinheimo, Sarah Holdsworth-Carson, Isabel C Hostettler, Henry Houlden, Sahar Houshdaran, Juan C Irwin, Marjo-Riitta Jarvelin, Yoichiro Kamatani, Stephen H Kennedy, Ewa Kepka, Johannes Kettunen, Michiaki Kubo, Bartosz Kulig, Venla Kurra, Hannele Laivuori, Marc R Laufer, Cecilia M Lindgren, Stuart MacGregor, Massimo Mangino, Nicholas G Martin, Charoula Matalliotaki, Michail Matalliotakis, Alison D Murray, Anne Ndungu, Camran Nezhat, Catherine M Olsen, Jessica Opoku-Anane, Sandosh Padmanabhan, Manish Paranjpe, Maire Peters, Grzegorz Polak, David J Porteous, Joseph Rabban, Kathyrn M Rexrode, Hanna Romanowicz, Merli Saare, Liisu Saavalainen, Andrew J Schork, Sushmita Sen, Amy L Shafrir, Anna Siewierska-Górska, Marcin Słomka, Blair H Smith, Beata Smolarz, Tomasz Szaflik, Krzysztof Szyłło, Atsushi Takahashi, Kathryn L Terry, Carla Tomassetti, Susan A Treloar, Arne Vanhie, Katy Vincent, Kim C Vo, David J Werring, Eleftheria Zeggini, Maria I Zervou, DBDS Genomic Consortium, FinnGen Study, FinnGen Endometriosis Taskforce, Celmatix Research Team, 23andMe Research Team, Sosuke Adachi, Julie E Buring, Paul M Ridker, Thomas D'Hooghe, George N Goulielmos, Dharani K Hapangama, Caroline Hayward, Andrew W Horne, Siew-Kee Low, Hannu Martikainen, Daniel I Chasman, Peter A W Rogers, Philippa T Saunders, Marina Sirota, Tim Spector, Dominik Strapagiel, Joyce Y Tung, David C Whiteman, Linda C Giudice, Digna R Velez-Edwards, Outi Uimari, Peter Kraft, Andres Salumets, Dale R Nyholt, Reedik Mägi, Kari Stefansson, Christian M Becker, Piraye Yurttas-Beim, Valgerdur Steinthorsdottir, Mette Nyegaard, Stacey A Missmer, Grant W Montgomery, Andrew P Morris, Krina T Zondervan Show less
Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and Show more
Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention. Show less
đź“„ PDF DOI: 10.1038/s41588-023-01323-z
MLLT10
John C Chambers, Weihua Zhang, Joban Sehmi +140 more · 2011 · Nature genetics · Nature · added 2026-04-24
John C Chambers, Weihua Zhang, Joban Sehmi, Xinzhong Li, Mark N Wass, Pim Van der Harst, Hilma Holm, Serena Sanna, Maryam Kavousi, Sebastian E Baumeister, Lachlan J Coin, Guohong Deng, Christian Gieger, Nancy L Heard-Costa, Jouke-Jan Hottenga, Brigitte Kühnel, Vinod Kumar, Vasiliki Lagou, Liming Liang, Jian'an Luan, Pedro Marques Vidal, Irene Mateo Leach, Paul F O'Reilly, John F Peden, Nilufer Rahmioglu, Pasi Soininen, Elizabeth K Speliotes, Xin Yuan, Gudmar Thorleifsson, Behrooz Z Alizadeh, Larry D Atwood, Ingrid B Borecki, Morris J Brown, Pimphen Charoen, Francesco Cucca, Debashish Das, Eco J C de Geus, Anna L Dixon, Angela Döring, Georg Ehret, Gudmundur I Eyjolfsson, Martin Farrall, Nita G Forouhi, Nele Friedrich, Wolfram Goessling, Daniel F Gudbjartsson, Tamara B Harris, Anna-Liisa Hartikainen, Simon Heath, Gideon M Hirschfield, Albert Hofman, Georg Homuth, Elina Hyppönen, Harry L A Janssen, Toby Johnson, Antti J Kangas, Ido P Kema, Jens P Kühn, Sandra Lai, Mark Lathrop, Markus M Lerch, Yun Li, T Jake Liang, Jing-Ping Lin, Ruth J F Loos, Nicholas G Martin, Miriam F Moffatt, Grant W Montgomery, Patricia B Munroe, Kiran Musunuru, Yusuke Nakamura, Christopher J O'Donnell, Isleifur Olafsson, Brenda W Penninx, Anneli Pouta, Bram P Prins, Inga Prokopenko, Ralf Puls, Aimo Ruokonen, Markku J Savolainen, David Schlessinger, Jeoffrey N L Schouten, Udo Seedorf, Srijita Sen-Chowdhry, Katherine A Siminovitch, Johannes H Smit, Timothy D Spector, Wenting Tan, Tanya M Teslovich, Taru Tukiainen, Andre G Uitterlinden, Melanie M Van der Klauw, Ramachandran S Vasan, Chris Wallace, Henri Wallaschofski, H-Erich Wichmann, Gonneke Willemsen, Peter Würtz, Chun Xu, Laura M Yerges-Armstrong, Alcohol Genome-wide Association (AlcGen) Consortium, Diabetes Genetics Replication and Meta-analyses (DIAGRAM+) Study, Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Global Lipids Genetics Consortium, Genetics of Liver Disease (GOLD) Consortium, International Consortium for Blood Pressure (ICBP-GWAS), Meta-analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), Goncalo R Abecasis, Kourosh R Ahmadi, Dorret I Boomsma, Mark Caulfield, William O Cookson, Cornelia M Van Duijn, Philippe Froguel, Koichi Matsuda, Mark I McCarthy, Christa Meisinger, Vincent Mooser, Kirsi H Pietiläinen, Gunter Schumann, Harold Snieder, Michael J E Sternberg, Ronald P Stolk, Howard C Thomas, Unnur Thorsteinsdottir, Manuela Uda, Gérard Waeber, Nicholas J Wareham, Dawn M Waterworth, Hugh Watkins, John B Whitfield, Jacqueline C M Witteman, Bruce H R Wolffenbuttel, Caroline S Fox, Mika Ala-Korpela, Kari Stefansson, Peter Vollenweider, Henry Völzke, Eric E Schadt, James Scott, Marjo-Riitta Järvelin, Paul Elliott, Jaspal S Kooner Show less
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 conc Show more
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. Show less
đź“„ PDF DOI: 10.1038/ng.970
FADS1