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- Acosta-Herrera, M, et al.
(author)
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Genome-wide meta-analysis reveals shared new loci in systemic seropositive rheumatic diseases
- 2019
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In: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 78:3, s. 311-319
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Journal article (peer-reviewed)abstract
- Immune-mediated inflammatory diseases (IMIDs) are heterogeneous and complex conditions with overlapping clinical symptoms and elevated familial aggregation, which suggests the existence of a shared genetic component. In order to identify this genetic background in a systematic fashion, we performed the first cross-disease genome-wide meta-analysis in systemic seropositive rheumatic diseases, namely, systemic sclerosis, systemic lupus erythematosus, rheumatoid arthritis and idiopathic inflammatory myopathies.MethodsWe meta-analysed ~6.5 million single nucleotide polymorphisms in 11 678 cases and 19 704 non-affected controls of European descent populations. The functional roles of the associated variants were interrogated using publicly available databases.ResultsOur analysis revealed five shared genome-wide significant independent loci that had not been previously associated with these diseases: NAB1, KPNA4-ARL14, DGQK, LIMK1 and PRR12. All of these loci are related with immune processes such as interferon and epidermal growth factor signalling, response to methotrexate, cytoskeleton dynamics and coagulation cascade. Remarkably, several of the associated loci are known key players in autoimmunity, which supports the validity of our results. All the associated variants showed significant functional enrichment in DNase hypersensitivity sites, chromatin states and histone marks in relevant immune cells, including shared expression quantitative trait loci. Additionally, our results were significantly enriched in drugs that are being tested for the treatment of the diseases under study.ConclusionsWe have identified shared new risk loci with functional value across diseases and pinpoint new potential candidate loci that could be further investigated. Our results highlight the potential of drug repositioning among related systemic seropositive rheumatic IMIDs.
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| 8. |
- Leclair, V, et al.
(author)
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HLA-DRB1 ASSOCIATIONS WITH AUTOANTIBODY-DEFINED SUBGROUPS IN IDIOPATHIC INFLAMMATORY MYOPATHIES (IIM)
- 2022
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In: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 81, s. 104-105
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Conference paper (other academic/artistic)abstract
- There is a gap between how IIM patients are classified in practice and current validated classification criteria1. Also, different associations with genetic variations in HLA can inform about different T-cell mechanisms involved in disease pathogenesis.ObjectivesWe aimed to systematically study associations between HLA-DRB1 alleles, clinical manifestations, and autoantibody-defined IIM subgroups.MethodsWe included 1348 IIM patients from five European countries. An unsupervised cluster analysis was performed using 14 autoantibodies: anti-Jo1, -PL7, -PL12, -EJ, -OJ, -SRP, -U1RNP, -Ro52, -Mi2, -TIF1γ, -MDA5, -PMScl, -SAE1, and -NXP2 to identify patients’ subgroups. Logistic regressions were used to estimate the associations between HLA-DRB1 alleles, clinical manifestations and the identified subgroups.ResultsEight subgroups were defined by the autoantibody status (Table 1). Three of the subgroups (1, 2 and 6) have overlapping autoantibodies, while four are almost monospecific (3,4,5 and 7), and one (8) has patients negative for tested autoantibodies. Figure 1 represents the significant associations between HLA-DRB1 alleles and the eight subgroups. Heliotrope rash and Gottron’s sign were significantly more frequent in subgroups 3 (OR:2.2 95%CI:[1.1-4.8], OR:2.6 95%CI:[1.3-5.9], respectively), 4 (OR:12 95%CI:[3.6-75], OR:7.8 95%CI:[2.8-33], respectively) and 7 (OR:22 95%CI:[4.5-385], OR:10 95%CI:[3.1-65], respectively), and Raynaud’s phenomenon was significantly more frequent in subgroup 6 (OR:3.3 95%CI:[1.2-11]).Table 1.Autoantibody-defined subgroups using an unsupervised cluster analysis.Subgroups/ MedoidsVariables1 Ro522 U1RNP3 PMScl4 Mi25 Jo16 Jo1/Ro527 TIF18 None*Alln (%)137 (10)183 (14)107 (8)65 (5)119 (9)140 (10)78 (6)519 (39)1348 (100)Female (%)93 (68)116 (63)79 (74)45 (69)76 (64)96 (69)64 (82)313 (60)882 (65)Age at diagnosis, median (IQR)56 (16)51.5 (23)51 (25)57 (22.5)47.5 (23.25)52 (19.5)53.5 (21.75)58 (22)55 (23)AutoantibodiesAnti-Jo106 (3)01 (2)119 (100)140 (100)00266 (20)Anti-PL77 (5)13 (7)00000020 (1.5)Anti-PL125 (4)3 (2)1 (1)01 (1)00010 (0.7)Anti-EJ2 (2)00000002 (0.1)Anti-OJ07 (4)0000007 (0.5)Anti-TIF110 (7)2 (1)2 (2)00078 (100)092 (7)Anti-Mi21 (1)1 (1)1 (1)65 (100)02 (1)0070 (5)Anti-SAE18 (6)23 (13)00000031 (2)Anti-NXP21 (1)23 (13)1 (1)0000025 (2)Anti-MDA59 (7)10 (6)1 (1)1 (2)01 (1)0022 (2)Anti-SRP8 (6)32 (18)00000040 (3)Anti-Ro52137 (100)16 (9)000140 (100)00293 (22)Anti-PMScl11 (8)1 (1)107 (100)00000119 (9)Anti-U1RNP079 (43)0003 (2)0082 (6)*IIM patients negative for the tested autoantibodies.Figure 1.Forest plot of significant associations of HLA. *DRB1 alleles with autoantibody-defined subgroups. Scandinavia includes patients from Denmark, Norway, and Sweden.ConclusionOur study reveals that certain subgroups of IIM patients are characterized by overlap of myositis -specific and -associated autoantibodies, which in turn are associated with different HLA-DRB1 alleles including potential novel associations. These results point to different disease mechanisms in the subgroups, as well as suggest that IIM classification could be improved by integrating broader serological and genetic data.References[1]Parker MJS, Oldroyd A, Roberts ME, et al. The performance of the European League Against Rheumatism/American College of Rheumatology idiopathic inflammatory myopathies classification criteria in an expert-defined 10 year incident cohort. Rheumatology (Oxford). 2019;58(3):468-475.AcknowledgementsWe thank all the patients who participated in the study.Disclosure of InterestsValerie Leclair: None declared, Angeles Shunashy Galindo-Feria: None declared, Simon Rothwell: None declared, Olga Kryštůfková: None declared, Heřman Mann: None declared, Louise Pyndt Diederichsen: None declared, helena andersson: None declared, Martin Klein: None declared, Sarah Tansley: None declared, Neil McHugh: None declared, Janine Lamb: None declared, Jiří Vencovský Speakers bureau: Abbvie, Biogen, Boehringer, Eli Lilly, Gilead, MSD, Novartis, Pfizer, Roche, Sanofi, UCB, Werfen, Consultant of: Abbvie, Argenx, Boehringer, Eli Lilly, Gilead, Octapharma, Pfizer, UCB, Grant/research support from: Abbvie, Hector Chinoy: None declared, Marie Holmqvist: None declared, Leonid Padyukov: None declared, Ingrid E. Lundberg Shareholder of: Roche and Novartis, Consultant of: Corbus Pharmaceuticals Inc, Astra Zeneca, Bristol Myer´s Squibb, Corbus Pharmaceutical, EMD Serono Research & Development Institute, Argenx, Octapharma, Kezaar, Orphazyme, and Janssen, Grant/research support from: Astra Zeneca, Lina M. Diaz-Gallo: None declared
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