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- Khatri, B., et al.
(author)
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Genome-wide association study identifies Sjogren's risk loci with functional implications in immune and glandular cells
- 2022
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1
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Journal article (peer-reviewed)abstract
- Sjogren's disease is a complex autoimmune disease with twelve established susceptibility loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant (GWS) regions in Sjogren's cases of European ancestry: CD247, NAB1, PTTG1-MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2, SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08. Interrogation of bioinformatics databases refine the associations, define local regulatory networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to >40. Many GWS SNPs are eQTLs for genes within topologically associated domains in immune cells and/or eQTLs in the main target tissue, salivary glands. The genetic architecture underlying Sjogren's syndrome is not fully understood. Here, the authors perform a genome-wide association study to identify 10 new genetic risk regions, implicating genes involved in immune and salivary gland function.
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- Langefeld, Carl D., et al.
(author)
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Transancestral mapping and genetic load in systemic lupus erythematosus
- 2017
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 8
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Journal article (peer-reviewed)abstract
- Systemic lupus erythematosus (SLE) is an autoimmune disease with marked gender and ethnic disparities. We report a large transancestral association study of SLE using Immunochip genotype data from 27,574 individuals of European (EA), African (AA) and Hispanic Amerindian (HA) ancestry. We identify 58 distinct non-HLA regions in EA, 9 in AA and 16 in HA (similar to 50% of these regions have multiple independent associations); these include 24 novel SLE regions (P < 5 x 10(-8)), refined association signals in established regions, extended associations to additional ancestries, and a disentangled complex HLA multigenic effect. The risk allele count (genetic load) exhibits an accelerating pattern of SLE risk, leading us to posit a cumulative hit hypothesis for autoimmune disease. Comparing results across the three ancestries identifies both ancestry-dependent and ancestry-independent contributions to SLE risk. Our results are consistent with the unique and complex histories of the populations sampled, and collectively help clarify the genetic architecture and ethnic disparities in SLE.
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- Brito-Zeron, P., et al.
(author)
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How immunological profile drives clinical phenotype of primary Sjögren's syndrome at diagnosis : analysis of 10,500 patients (Sjögren Big Data Project)
- 2018
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In: Clinical and Experimental Rheumatology. - : CLINICAL & EXPER RHEUMATOLOGY. - 0392-856X .- 1593-098X. ; 36:3, s. S102-S112
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Journal article (peer-reviewed)abstract
- Objective: To evaluate the influence of the main immunological markers on the disease phenotype at diagnosis in a large international cohort of patients with primary Sjogren's syndrome (SjS).Methods: The Big Data Sjogren Project Consortium is an international, multicentre registry created in 2014. As a first step, baseline clinical information from leading centres on clinical research in SjS of the 5 continents was collected. The centres shared a harmonised data architecture and conducted cooperative online efforts in order to refine collected data under the coordination of a big data statistical team. Inclusion criteria were the fulfillment of the 2002 classification criteria. Immunological tests were carried out using standard commercial assays.Results: By January 2018, the participant centres had included 10,500 valid patients from 22 countries. The cohort included 9,806 (93%) women and 694 (7%) men, with a mean age at diagnosis of primary SjS of 53 years, mainly White (78%) and included from European countries (71%). The frequency of positive immunological markers at diagnosis was 79.3% for ANA, 73.2% for anti-Ro, 48.6% for RF, 45.1% for anti-La, 13.4% for low C3 levels, 14.5% for low C4 levels and 7.3% for cryoglobulins. Positive autoantibodies (ANA, Ro, La) correlated with a positive result in salivary gland biopsy, while hypocomplementaemia and especially cryoglobulinaemia correlated with systemic activity (mean ESSDAI score of 17.7 for ctyoglobulins, 11.3 for low C3 and 9.2 for low C4, in comparison with 3.8 for negative markers). The immunological markers with a great number of statistically-significant associations (p<0.001) in the organ-by-organ ESSDAI evaluation were cryoglobulins (9 domains), low C3 (8 domains), anti-La (7 domains) and low C4 (6 domains).Conclusion: We confirm the strong influence of immunological markers on the phenotype of primary SjS at diagnosis in the largest multi-ethnic international cohort ever analysed, with a greater influence for cryoglobulinaemic-related markers in comparison with Ro/La autoantibodies and ANA. Immunological patterns play a central role in the phenotypic expression of the disease already at the time of diagnosis, and may guide physicians to design a specific personalised management during the follow-up of patients with primary SjS.
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- Aghakhanian, F, et al.
(author)
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INTEGRATION OF GWAS AND EPIGENETIC STUDIES IDENTIFIES NOVEL GENES THAT ALTER EXPRESSION IN THE MINOR SALIVARY GLAND IN SJOGREN'S DISEASE
- 2022
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In: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 81, s. 72-73
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Conference paper (other academic/artistic)abstract
- Sjogren’s disease (SjD) is an autoimmune disease characterized by reduced function of exocrine glands (i.e., salivary and lacrimal glands). Epithelial cell damage resulting from lymphocytic infiltration has been implicated in SjD etiology [1]. How genetic and epigenetic changes influence epithelial-immune cell interactions in SjD pathogenesis remain understudied.ObjectivesEvaluate the role of SjD risk loci in salivary gland tissue to gain insights into the potential genes involved in salivary gland dysfunction.MethodsSNPs from 16 regions with SNP-SjD associations (P<5x10-8) in our GWAS study (3232 SjD cases) and meta-analysis of ImmunoChip data (619 SjD cases) [2] were interrogated for eQTLs using Genotype-Tissue Expression (GTEx) minor salivary gland data. Subsequent analysis identified genes that were both eQTLs in the minor salivary gland and significantly expressed in RNA-seq and ATAC-seq data from the submaxillary salivary gland epithelial cell line, A253. Pathway enrichment analysis was performed using gProfiler on the genes where coalescence of eQTL, RNA-seq, and ATAC-seq data was observed. To further validate the results, we performed transcriptome-wide association study (TWAS) analysis using GWAS summary statistics and minor salivary gland eQTL GTEx data.ResultsIn total, 5884 genome-wide significant SNPs from 16 SjD risk loci were identified as potential minor salivary gland eQTLs using two discovery thresholds: p(FDR)<0.05 provided by eQTL study (3566 SNPs) and p(FDR)>0.05 and p<0.05 in eQTL study (2318 SNPs). Further analysis revealed 10 SjD risk loci with SNPs that were minor salivary gland eQTLs for a total of 155 unique genes that had a coalescence of RNA- and ATAC-seq data in A253 cells. Many SNPs altered the expression of the nearest gene to the risk allele (i.e., index gene), such as IRF5 and TNPO3 on chromosome 7 at 128Mb; however, this locus had 12 additional genes that were eQTLs in minor salivary gland. In contrast, other loci had no reported eQTLs for the index gene, but several reported eQTLs for other genes, such TYK2 on chromosome 19 at 10Mb that showed no change in TYK2 expression but eQTLs for 8 distant genes, including ICAM1. Pathway enrichment analysis revealed an enrichment in Butyrophilin (BTN) family interactions (R-HSA-8851) (PAdj=1.564x10-5), including the BTN2A1, BTN2A2, BTN3A1, BTN3A2 and BTN3A3 gene cluster in the MHC region. In further support, TWAS of the minor salivary gland and the SjD GWAS summary statistics (after Bonferroni correction) showed association between SjD and BTN3A2 (p=1.24x10-42), as well as many other loci in the MHC region. In addition, several long non-coding (lnc) RNAs on chromosome 17 were significant, peaking at RP11-259G18.1 (p=4.43x10-10).ConclusionThis study shows that SjD-associated risk alleles influence disease by altering gene expression in immune cells and minor salivary glands. Further, our analysis suggests that altered gene expression in the minor salivary gland expands beyond effects on the index gene to several genes on each locus. Interestingly, we observed minor salivary gland eQTLs for several BTN family genes, which act as cell-surface binding partners to regulate cell-cell interactions, including interactions between epithelial cells and activated T cells [3]. Future work will assess chromatin-chromatin-interactions within the 10 SjD risk loci in salivary gland cells and tissues to map local chromatin regulatory networks that regulate gene expression. Additional transcriptional studies of SjD minor salivary gland tissues will provide further insights into how altered gene expression in the salivary gland influences SjD pathology.References[1]Verstappen. Nat Rev Rheumatol 2021;17(6):333-348.[2]Khatri, et al. Annals of Rheumatic Diseases 2020;79:30-31.[3]Arnett HA, Viney JL. Nature Reviews Immunology 2014;14:559-569.Disclosure of InterestsFarhang Aghakhanian: None declared, Mandi M Wiley: None declared, Bhuwan Khatri: None declared, Kandice L Tessneer: None declared, Astrid Rasmussen: None declared, Simon J. Bowman Consultant of: Abbvie, Galapagos, and Novartis in 2020-2021., Lida Radfar: None declared, Roald Omdal: None declared, Marie Wahren-Herlenius: None declared, Blake M Warner: None declared, Torsten Witte: None declared, Roland Jonsson: None declared, Maureen Rischmueller: None declared, Patrick M Gaffney: None declared, Judith A. James: None declared, Lars Ronnblom: None declared, R Hal Scofield: None declared, Xavier Mariette: None declared, Marta Alarcon-Riquelme: None declared, Wan Fai Ng: None declared, Kathy Sivils Employee of: Current employee of Janssen, Gunnel Nordmark: None declared, Umesh Deshmukh: None declared, A Darise Farris: None declared, Christopher Lessard: None declared
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- Kottyan, Leah C., et al.
(author)
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The IRF5-TNPO3 association with systemic lupus erythematosus has two components that other autoimmune disorders variably share.
- 2015
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 24:2, s. 582-596
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Journal article (peer-reviewed)abstract
- Exploiting genotyping, DNA sequencing, imputation and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5-TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE), we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3230 IRF5-TNPO3 high-quality, common variants across 5 ethnicities in 8395 SLE cases and 7367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (P-valuemeta = 6 × 10(-49); OR = 1.38-1.97). The second genetic effect spanned an 85.5-kb, 24-variant haplotype that included the genes IRF5 and TNPO3 (P-valuesEU = 10(-27)-10(-32), OR = 1.7-1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögrens syndrome and systemic sclerosis whereas only the IRF5-TNPO3 gene-spanning haplotype is associated with primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5-TNPO3.
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- Wiley, MM, et al.
(author)
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SJOGREN'S DISEASE AND SYSTEMIC LUPUS ERYTHEMATOSUS DDX6-CXCR5 RISK INTERVALS REVEAL COMMON SNPS WITH FUNCTIONAL SIGNIFICANCE IN IMMUNE AND SALIVARY GLAND CELLS
- 2022
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In: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 81, s. 269-270
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Conference paper (other academic/artistic)abstract
- Sjögren’s Disease (SjD) and Systemic Lupus Erythematosus (SLE) are autoimmune diseases with several shared characteristics and similar genome-wide significant associations with the DDX6-CXCR5 locus. DDX6 suppresses interferon-stimulated gene expression and CXCR5 regulates T cell functions implicated in autoimmunity.ObjectivesTo identify and characterize functional SNPs in the DDX6-CXCR5 interval.MethodsImmunoChip data from European populations (3785 SLE cases; 1916 SjD cases; 6893 controls) were imputed and SNP-trait associations tested. Bayesian statistics defined a credible SNP set that was refined using bioinformatic analyses (RegulomeDB, Haploreg, ENCODE, promoter capture Hi-C, eQTLs, etc.). Electrophoretic mobility shift assays (EMSAs) and luciferase expression assays were used to test allele-specific SNP function in EBV-transformed B (EBV B) cells, Daudi B cells, Jurkat T cells, THP1 monocytes, and A253 salivary gland cell lines. Chromatin conformation capture with quantitative PCR (3C-qPCR) was used to assess long-range chromatin interactions.ResultsFine mapping of the SjD and SLE associations found similar SNP associations. Bioinformatic analyses identified 5 common SNPs with strong evidence of functionality in immune cell types: rs57494551 in an intron of DDX6, and rs4938572, rs4936443, rs7117261, and rs4938573 in the promoter/enhancer region of DDX6 and CXCR5. EMSAs and luciferase experiments showed cell type-specific differences in protein binding and promoter or enhancer activity, respectively, at each SNP. Risk allele of rs57494551 increased enhancer activity in B cells and A253 cells (p<0.001), but decreased promoter activity in T cells and A253 cells (p<0.01). SNP rs4938572 is an eQTL of DDX6 in T cells, and the risk allele significantly increased protein binding, promoter and enhancer activity in T cells (p<0.01). Risk allele of rs4938572 also increased promoter activity in A253 cells (p<0.001), but had no effect on promoter or enhancer activity in B cells. SNP rs4936443 showed no promoter or enhancer activity in immune cells, but the risk allele showed significant promoter and enhancer (p<0.001) activity in A253 cells. SNP rs7117261 showed decreased enhancer activity in EBV B cells, T cells, and A253 cells (p<0.05) and increased promoter activity in A253 cells (p<0.001). SNP rs4938573 showed decreased promoter activity in EBV B cells, T cell and A253 cells (p<0.05), decreased promoter activity in EBV B cells (p<0.05), and increased enhancer activity in A253 cells (p<0.0001). Overall, A253 cells exhibited more allele-specific effects on promoter and enhancer activity across the five SNPs compared to tested immune cells. In addition to DDX6 and CXCR5, rs57494551 and/or rs4938572 are reported eQTLs for several other genes of interest in the local chromatin regulatory network: IL10RA in T cells, TRAPPC4 in salivary gland and activated macrophages, and long non-coding (lnc)RNA AP002954.1 in T cells and whole blood. 3C-qPCR in EBV B and A253 cells showed that the two regulatory regions carrying rs4938572 or rs57494551 interacted with a region upstream of DDX6 that includes AP002954.1. Hi-C data showed looping between AP002954.1 and the regulatory region carrying rs4938572 and rs57494551 in T cells.ConclusionSjD and SLE share similar genomic architecture across the DDX6-CXCR5 risk interval with several common SNPs showing immune and salivary gland cell type-specific allelic effects on protein binding and/or enhancer/promoter activity. Extensive bioinformatic analyses suggest that the SNPs likely work within the local chromatin regulatory network to regulate cell type-specific expression of several genes on the interval. Ongoing studies will use 3C-qPCR to assess allele-specific chromatin interactions between the SNPs and these genes in different cells types, and CRISPR to determine how the risk alleles alters expression.Disclosure of InterestsMandi M Wiley: None declared, Bhuwan Khatri: None declared, Kandice L Tessneer: None declared, Michelle L Joachims: None declared, Anna M Stolarczyk: None declared, Anna Nagel: None declared, Astrid Rasmussen: None declared, Simon J. Bowman Consultant of: Abbvie, Galapagos, and Novartis in 2020-2021, Lida Radfar: None declared, Roald Omdal: None declared, Marie Wahren-Herlenius: None declared, Blake M Warner: None declared, Torsten Witte: None declared, Roland Jonsson: None declared, Maureen Rischmueller: None declared, Patrick M Gaffney: None declared, Judith A. James: None declared, Lars Ronnblom: None declared, R Hal Scofield: None declared, Xavier Mariette: None declared, Wan Fai Ng: None declared, Kathy Sivils Employee of: current employee of Janssen., Gunnel Nordmark: None declared, Betty Tsao: None declared, Christopher Lessard: None declared
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