Interferons in Sjögren’s Syndrome: Genes, Mechanisms, and Effects

Sjögren’s syndrome (SS) is a common, progressive autoimmune exocrinopathy distinguished by dry eyes and mouth and affects ∼0.7% of the European population. Overexpression of transcripts induced by interferons (IFN), termed as an “IFN signature,” has been found in SS patients. Four microarray studies have been published in SS that identified dysregulated genes within type I IFN signaling in either salivary glands or peripheral blood of SS patients. The mechanism of this type I IFN activation is still obscure, but several possible explanations have been proposed, including virus infection-initiated and immune complex-initiated type I IFN production by plasmacytoid dendritic cells. Genetic predisposition to increased type I IFN signaling is supported by candidate gene studies showing evidence for association of variants within IFN-related genes. Once activated, IFN signaling may contribute to numerous aspects of SS pathophysiology, including lymphocyte infiltration into exocrine glands, autoantibody production, and glandular cell apoptosis. Thus, dysregulation of IFN pathways is an important feature that can be potentially used as a serum biomarker for diagnosis and targeting of new treatments in this complex autoimmune disease

Detrimental effects of duplicate reads and low complexity regions on RNA- and ChIP-seq data

Background Adapter trimming and removal of duplicate reads are common practices in next-generation sequencing pipelines. Sequencing reads ambiguously mapped to repetitive and low complexity regions can also be problematic for accurate assessment of the biological signal, yet their impact on sequencing data has not received much attention. We investigate how trimming the adapters, removing duplicates, and filtering out reads overlapping low complexity regions influence the significance of biological signal in RNA- and ChIP-seq experiments. Methods We assessed the effect of data processing steps on the alignment statistics and the functional enrichment analysis results of RNA- and ChIP-seq data. We compared differentially processed RNA-seq data with matching microarray data on the same patient samples to determine whether changes in pre-processing improved correlation between the two. We have developed a simple tool to remove low complexity regions, RepeatSoaker, available at https://github.com/mdozmorov/RepeatSoaker, and tested its effect on the alignment statistics and the results of the enrichment analyses. Results Both adapter trimming and duplicate removal moderately improved the strength of biological signals in RNA-seq and ChIP-seq data. Aggressive filtering of reads overlapping with low complexity regions, as defined by RepeatMasker, further improved the strength of biological signals, and the correlation between RNA-seq and microarray gene expression data. Conclusions Adapter trimming and duplicates removal, coupled with filtering out reads overlapping low complexity regions, is shown to increase the quality and reliability of detecting biological signals in RNA-seq and ChIP-seq data

Familial Aggregation of High Tumor Necrosis Factor Alpha Levels in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) patients frequently have high circulating tumor necrosis factor alpha (TNF-α) levels. We explored circulating TNF-α levels in SLE families to determine whether high levels of TNF-α were clustered in a heritable pattern. We measured TNF-α in 242 SLE patients, 361 unaffected family members, 23 unaffected spouses of SLE patients, and 62 unrelated healthy controls. Familial correlations and relative recurrence risk rates for the high TNF-α trait were assessed. SLE-affected individuals had the highest TNF-α levels, and TNF-α was significantly higher in unaffected first degree relatives than healthy unrelated subjects (P=0.0025). No Mendelian patterns were observed, but 28.4% of unaffected first degree relatives of SLE patients had high TNF-α levels, resulting in a first degree relative recurrence risk of 4.48 (P=2.9×10-5). Interestingly, the median TNF-α value in spouses was similar to that of the first degree relatives. Concordance of the TNF-α trait (high versus low) in SLE patients and their spouses was strikingly high at 78.2%. These data support a role for TNF-α in SLE pathogenesis, and TNF-α levels may relate with heritable factors. The high degree of concordance in SLE patients and their spouses suggests that environmental factors may also play a role in the observed familial aggregation

ABIN1 dysfunction as a genetic basis for lupus nephritis

The genetic factors underlying the pathogenesis of lupus nephritis associated with systemic lupus erythematosus are largely unknown, although animal studies indicate that nuclear factor (NF)-?B is involved. We reported previously that aknockin mouse expressinganin active form of ABIN1 (ABIN1[D485N]) develops lupus-like autoimmune disease and demonstrates enhanced activation of NF-?B and mitogen-activated protein kinases in immune cells after toll-like receptor stimulation. In the current study, we show that ABIN1[D485N] mice develop progressive GN similar to class III and IV lupus nephritis in humans. To investigate the clinical relevance of ABIN1 dysfunction, we genotyped five single-nucleotide polymorphisms in the gene encoding ABIN1, TNIP1, in samples from European-American, African American, Asian, Gullah, and Hispanic participants in the Large Lupus Association Study 2. Comparing cases of systemic lupus erythematosus with nephritis and cases ofsystemic lupus erythematosus without nephritis revealed strong associations with lupus nephritis at rs7708392 in European Americans and rs4958881 in African Americans. Comparing cases of systemic lupus erythematosus with nephritis and healthy controls revealed a stronger association at rs7708392 in European Americans but not at rs4958881 in African Americans. Our data suggest that variants in the TNIP1 gene are associated with the risk for lupus nephritis and could be mechanistically involved in disease development via aberrant regulation of NF-?B and mitogen-activated protein kinase activity. Copyright © 2013 by the American Society of Nephrology

Preferential binding to elk-1 by sle-associated il10 risk allele upregulates il10 expression

Immunoregulatory cytokine interleukin-10 (IL-10) is elevated in sera from patients with systemic lupus erythematosus (SLE) correlating with disease activity. The established association of IL10 with SLE and other autoimmune diseases led us to fine map causal variant(s) and to explore underlying mechanisms. We assessed 19 tag SNPs, covering the IL10 gene cluster including IL19, IL20 and IL24, for association with SLE in 15,533 case and control subjects from four ancestries. The previously reported IL10 variant, rs3024505 located at 1 kb downstream of IL10, exhibited the strongest association signal and was confirmed for association with SLE in European American (EA) (P = 2.7×10−8, OR = 1.30), but not in non-EA ancestries. SNP imputation conducted in EA dataset identified three additional SLE-associated SNPs tagged by rs3024505 (rs3122605, rs3024493 and rs3024495 located at 9.2 kb upstream, intron 3 and 4 of IL10, respectively), and SLE-risk alleles of these SNPs were dose-dependently associated with elevated levels of IL10 mRNA in PBMCs and circulating IL-10 protein in SLE patients and controls. Using nuclear extracts of peripheral blood cells from SLE patients for electrophoretic mobility shift assays, we identified specific binding of transcription factor Elk-1 to oligodeoxynucleotides containing the risk (G) allele of rs3122605, suggesting rs3122605 as the most likely causal variant regulating IL10 expression. Elk-1 is known to be activated by phosphorylation and nuclear localization to induce transcription. Of interest, phosphorylated Elk-1 (p-Elk-1) detected only in nuclear extracts of SLE PBMCs appeared to increase with disease activity. Co-expression levels of p-Elk-1 and IL-10 were elevated in SLE T, B cells and monocytes, associated with increased disease activity in SLE B cells, and were best downregulated by ERK inhibitor. Taken together, our data suggest that preferential binding of activated Elk-1 to the IL10 rs3122605-G allele upregulates IL10 expression and confers increased risk for SLE in European Americans

Genome-wide association study identifies Sjögren’s risk loci with functional implications in immune and glandular cells

Sjögren’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 Sjögren’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.Research reported in this publication was supported by the National Institutes of Health (NIH): R01AR073855 (C.J.L.), R01AR065953 (C.J.L.), R01AR074310 (A.D.F.), P50AR060804 (K.L.S.), R01AR050782 (K.L.S), R01DE018209 (K.L.S.), R33AR076803 (I.A.), R21AR079089 (I.A.); NIDCR Sjögren’s Syndrome Clinic and Salivary Disorders Unit were supported by NIDCR Division of Intramural Research at the National Institutes of Health funds - Z01-DE000704 (B.W.); Birmingham NIHR Biomedical Research Centre (S.J.B.); Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2155 – Projektnummer 390874280 (T.W.); Research Council of Norway (Oslo, Norway) – Grant 240421 (TR.R.), 316120 (M.W-H.); Western Norway Regional Health Authority (Helse Vest) – 911807, 912043 (R.O.); Swedish Research Council for Medicine and Health (L.R., G.N., M.W-H.); Swedish Rheumatism Association (L.R., G.N., M.W-H.); King Gustav V’s 80-year Foundation (G.N.); Swedish Society of Medicine (L.R., G.N., M.W-H.); Swedish Cancer Society (E.B.); Sjögren’s Syndrome Foundation (K.L.S.); Phileona Foundation (K.L.S.). The Stockholm County Council (M.W-H.); The Swedish Twin Registry is managed through the Swedish Research Council - Grant 2017-000641. The French ASSESS (Atteinte Systémique et Evolution des patients atteints de Syndrome de Sjögren primitive) was sponsored by Assistance Publique-Hôpitaux de Paris (Ministry of Health, PHRC 2006 P060228) and the French society of Rheumatology (X.M.).publishedVersio

Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren’s syndrome

Sjögren’s syndrome is a common autoimmune disease (~0.7% of European Americans) typically presenting as keratoconjunctivitis sicca and xerostomia. In addition to strong association within the HLA region at 6p21 (Pmeta=7.65×10−114), we establish associations with IRF5-TNPO3 (Pmeta=2.73×10−19), STAT4 (Pmeta=6.80×10−15), IL12A (Pmeta =1.17×10−10), FAM167A-BLK (Pmeta=4.97×10−10), DDX6-CXCR5 (Pmeta=1.10×10−8), and TNIP1 (Pmeta=3.30×10−8). Suggestive associations with Pmeta<5×10−5 were observed with 29 regions including TNFAIP3, PTTG1, PRDM1, DGKQ, FCGR2A, IRAK1BP1, ITSN2, and PHIP amongst others. These results highlight the importance of genes involved in both innate and adaptive immunity in Sjögren’s syndrome

Genome-wide association study identifies Sjögren's risk loci with functional implications in immune and glandular cells.

Sjögren’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 Sjögren’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.We thank all the research and clinical staff, consortium investigators, and study participants (detailed in Supplementary Information), and funding agencies who made this study possible. The content of this publication is solely the responsibility of the authors and does not represent the official views of the funding agencies listed below. Research reported in this publication was supported by the National Institutes of Health (NIH): R01AR073855 (C.J.L.), R01AR065953 (C.J.L.), R01AR074310 (A.D.F.), P50AR060804 (K.L.S.), R01AR050782 (K.L.S), R01DE018209 (K.L.S.), R33AR076803 (I.A.), R21AR079089 (I.A.); NIDCR Sjögren’s Syndrome Clinic and Salivary Disorders Unit were supported by NIDCR Division of Intramural Research at the National Institutes of Health funds - Z01-DE000704 (B.W.); Birmingham NIHR Biomedical Research Centre (S.J.B.); Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2155 – Projektnummer 390874280 (T.W.); Research Council of Norway (Oslo, Norway) – Grant 240421 (TR.R.), 316120 (M.W-H.); Western Norway Regional Health Authority (Helse Vest) – 911807, 912043 (R.O.); Swedish Research Council for Medicine and Health (L.R., G.N., M.W-H.); Swedish Rheumatism Association (L.R., G.N., M.W-H.); King Gustav V’s 80-year Foundation (G.N.); Swedish Society of Medicine (L.R., G.N., M.W-H.); Swedish Cancer Society (E.B.); Sjögren’s Syndrome Foundation (K.L.S.); Phileona Foundation (K.L.S.). The Stockholm County Council (M.W-H.); FOREUM Foundation for Research in Rheumatology (R.J., M.W-H). The Swedish Twin Registry is managed through the Swedish Research Council - Grant 2017-000641. The French ASSESS (Atteinte Systémique et Evolution des patients atteints de Syndrome de Sjögren primitive) was sponsored by Assistance Publique-Hôpitaux de Paris (Ministry of Health, PHRC 2006 P060228) and the French society of Rheumatology (X.M.). We want to acknowledge the following invesigators who recruited patients: Jacques-Eric Gottenberg, Valerie Devauchelle-Pensec, Jean Jacques Dubost, Anne-Laure Fauchais, Vincent Goeb, Eric Hachulla, Claire Larroche, Véronique Le Guern, Jacques Morel, Aleth Perdriger, Emmanuelle Dernis, Stéphanie Rist, Damien Sene, Olivier Vittecoq. We also thank Sarah Tubiana and all staff members of the Bichat Hospital Biological Resource Center (Paris) for centralizing and managing biological collection. We also thank Rezvan Kiani Dehkordi, Karolina Tandre, Käth Nilsson, Marianne Eidsheim, Kjerstin Jacobsen, Ingeborg Kvivik and Kjetil Bårdsen for collecting patient blood samples. We acknowledge the SNP&SEQ Technology Platform, Uppsala, part of National Genomics Infrastructure (NGI) Sweden, for genotyping of Scandinavian samples, and the Swedish Twin Registry for access to data. The SNP&SEQ Technology Platform was supported by Science for Life Laboratory, Uppsala University, the Knut and Alice Wallenberg Foundation and the Swedish Research Council. Last, we thank the investigators for the following dbGaP studies: Phs000428.v2.p2: This study used control data from the Health and Retirement Study in dbGaP (phs000428.v2.p2) submitted by David Weir, PhD at the University of Michigan and funded by the National Institute of Aging RC2 AG036495 and RC4 AG039029. Phs000672.v1.p1: Genotype data from the Sjögren’s International Collaborative Clinical Alliance (SICCA) Registry was obtained through dbGAP accession number phs000672.v1.p1. This study was supported by the National Institute of Dental and Craniofacial Research (NIDCR), the National Eye Institute, and the Office of Research on Women’s Health through contract number N01-DE-32636. Genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health (NIH) to the Johns Hopkins University (contract numbers HHSN268200782096C, HHSN268201100011I, HHSN268201200008I). Funds for genotyping were provided by the NIDCR through CIDR’s NIH contract. Assistance with data cleaning and imputation was provided by the University of Washington. We thank investigators from the following studies that provided DNA samples for genotyping: the Genetic Architecture of Smoking and Smoking Cessation, Collaborative Genetic Study of Nicotine Dependence (phs000404.v1.p1); Age-Related Eye Disease Study (AREDS) - Genetic Variation in Refractive Error Substudy (phs000429.v1.p1); and National Institute of Mental Health’s Human Genetics Initiative (phs000021.v3.p2, phs000167.v1.p1). We thank the many clinical collaborators and research participants who contributed to this research. Phs000196.v3.p1: Investigators and Parkinson Disease patients that contributed to this Genome-wide Association Study of Parkinson Disease. phs000187.v1.p1: Research support to collect data and develop an application to support the High Density SNP Association Analysis of Melanoma project was provided by 3P50CA093459, 5P50CA097007, 5R01ES011740, and 5R01CA133996