ABSTRACT Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease in which the type I interferon pathway has a crucial role. We have previously shown that three genes in this

pathway, _IRF5, TYK2_ and _STAT4_, are strongly associated with risk for SLE. Here, we investigated 78 genes involved in the type I interferon pathway to identify additional SLE

susceptibility loci. First, we genotyped 896 single-nucleotide polymorphisms in these 78 genes and 14 other candidate genes in 482 Swedish SLE patients and 536 controls. Genes with

_P_<0.01 in the initial screen were then followed up in 344 additional Swedish patients and 1299 controls. SNPs in the _IKBKE, TANK, STAT1, IL8_ and _TRAF6_ genes gave nominal signals of

_STAT1_ was also associated with SLE in this cohort (_P_meta=3.3 × 10−5), but this association signal appears to be dependent of that previously reported for the neighbouring _STAT4_ gene.

Our study suggests additional genes from the type I interferon system in SLE, and highlights genes in this pathway for further functional analysis. SIMILAR CONTENT BEING VIEWED BY OTHERS

GWAS FOR SYSTEMIC SCLEROSIS IDENTIFIES SIX NOVEL SUSCEPTIBILITY LOCI INCLUDING ONE IN THE FCΓ RECEPTOR REGION Article Open access 31 January 2024 GENETICS OF SLE: MECHANISTIC INSIGHTS FROM

MONOGENIC DISEASE AND DISEASE-ASSOCIATED VARIANTS Article 12 July 2023 THE _ZNF76_ RS10947540 POLYMORPHISM ASSOCIATED WITH SYSTEMIC LUPUS ERYTHEMATOSUS RISK IN CHINESE POPULATIONS Article

Open access 04 March 2021 INTRODUCTION Systemic Lupus Erythematosus (SLE, OMIM 152700) is an inflammatory autoimmune disease that primarily affects women during their childbearing years.

Production of autoantibodies, tissue deposits of immune complexes and inflammation in kidneys, skin, joints and central nervous system are hallmarks of SLE. Despite a strong heritability of

the disease, linkage studies have failed to identify genes outside the major histocompatibility complex (MHC) region as risk factors for SLE. Association studies have since proven a more

fruitful approach. The confirmed findings from genomewide association studies (GWAS) include genes that were originally discovered in candidate gene studies, such as the interferon

regulatory factor 5 (IRF5)1 and the signal transducer and activator of transcription 4 (_STAT4_)2 genes from the type I IFN system. IFNs are cytokines with antiviral activity that are

produced in response to viral infections, of which the type I IFNs bind the IFN-α receptor (IFNAR). Today there are more than 20 confirmed SLE susceptibility loci,3, 4 of which several are

in the type I IFN system. The type I IFN system is activated in SLE patients,5, 6 and an important role of the type I IFN system in the disease process was confirmed by studies showing an

increased expression of type I IFN-inducible genes in SLE patients (an ‘IFN-signature’).7 A direct causative role of the type I IFN system in the etiopathogenesis of SLE was suggested by the

observation that individuals treated with IFN-_α_ can develop an SLE syndrome indistinguishable from the naturally occurring disease.8 Moreover, a phase I clinical trial with a monoclonal

antibody against IFN-_α_, reports reduction of disease activity as well as neutralization of the IFN signature in SLE patients.9, 10 Encouraged by the compelling evidence for the involvement

of the type I IFN system in SLE, we performed an association study to identify additional genes from the type I IFN pathway that confer risk for SLE. MATERIALS AND METHODS SUBJECTS AND

GENOTYPING Our study included 826 Swedish and 1310 US SLE patients, fulfilling at least four of the classification criteria for SLE as defined by the American College of Rheumatology

(ACR),11 and 9694 healthy control individuals from the same geographic areas as the patients (Supplementary Table S1). DNA was extracted from blood samples of the patients and controls using

standard procedures. The study was approved by the regional ethical boards and all subjects gave their informed consent to participate. The study was performed in three stages: DISCOVERY

PHASE First, a panel of SNPs in 82 genes with key functions related to the type I IFN signalling system and 14 additional genes, with suggested association with SLE, were selected for

genotyping in 490 Swedish SLE patients and 543 controls. Patients were from the rheumatology clinics at the Lund, Karolinska (Solna) and Uppsala University Hospitals in Sweden. SNPs were

selected on the basis of their average spacing of around 1 kb and LD information from the HapMap project (_r_2<0.8 HapMap CEU release 16c), excluding SNPs with an Illumina quality score

<0.6. Genotyping of 1258 SNPs in the 96 genes was performed using the Golden Gate Assay (Illumina Inc., San Diego, CA, USA). Samples and SNPs with >10% missing data, SNPs with

Hardy–Weinberg equilibrium test _P_-values <0.001 and SNPs with MAF <0.01 were excluded from further analysis. Four parent–offspring trios were included in the genotyping for

inheritance checks, and no Mendelian inheritance errors were observed. After exclusion of genetic outliers, duplicate or related samples 482 cases, 536 controls and 896 SNPs in 92 genes were

available for analysis. CONFIRMATORY SET In the second phase, SNPs in the eight most promising genes were followed up in 393 patients and 1645 controls from Sweden. Patients were from the

rheumatology clinics at the Umeå, Uppsala and Karolinska (Solna) University Hospitals. For the patients and 972 of the controls, genotyping of 25 SNPs was performed using the 12-plex and

48-plex SNPStream systems12 (Beckman Coulter Inc., Brea, CA, USA). Primer sequences are provided in Supplementary Table S2. The same quality control filters as for the discovery cohort were

applied, and samples overlapping with the discovery phase were excluded. Additional Swedish population-based controls from the Stockholm area (_n_=673), previously genotyped using the

Infinium II assay on human 1M v1 bead arrays13 (Illumina Inc.), were also included after applying the following quality filters: MAF>1%, HWE _P_>1 × 10−6, SNP and sample call rates

>95%. After exclusion of genetic outliers, duplicate or related samples, a total of 344 cases, 1299 controls and 21 SNPs were available for analysis. GWAS We sought replication of our

results by using data from a GWAS on SLE in US Caucasians.14 In brief, 1435 North-American SLE cases of European descent and 3583 controls had been genotyped on HumanHap550 bead arrays

(Illumina Inc.). An additional 4564 controls were also included as previously described.4 After strict quality control14 1310 cases and 7859 controls remained. ADDITIONAL QUALITY CONTROL AND

IMPUTATION For the 673 Swedish controls genotyped on the 1M bead arrays, genotypes for 13 confirmatory phase SNPs that were not directly genotyped were imputed using the software IMPUTE and

phasing data from the HapMap project.15 In the US GWAS dataset genotypes were imputed for 15 SNPs using the IMPUTE software. SNPs had imputation confidence scores ≥0.90 with one exception

(rs4694178, confidence 0.85 in the US data). For all the Swedish SLE patients, and for more than half of the Swedish controls genotyped using the GoldenGate or SNPstream methods, data from

6060 uncorrelated ancestry informative markers (AIMs) became available during the course of our study.4 Using this data, genetic outliers were identified with principal component analysis by

the EIGENSTRAT software16 and excluded from the study (the ten first principal components were inferred and a cut-off of _σ_>6 was used to identify outliers). These samples were also

checked for cryptic relatedness by investigation of identity-by-state (IBS) status in PLINK17 (http://pngu.mgh.harvard.edu/purcell/plink/) using a set of 12k previously genotyped SNPs. For

the Swedish controls, genotyped on the 1M arrays, all markers were used to identify cryptically related samples and 6035 successfully genotyped AIMs were used to identify genetic outliers.

ASSOCIATION ANALYSIS AND POWER CALCULATION The association analysis of the directly genotyped SNPs was performed by comparing allele frequencies in cases and controls with Fisher's

exact or Chi2 tests using PLINK. A null distribution for the quantile–quantile (Q–Q) plot was generated with PLINK and plotted using R (http://www.r-project.org/). Analyses including imputed

genotypes were performed using SNPTEST,15 which takes imputation uncertainty into account. SNPs, which were not captured by imputation were only analysed in the directly genotyped samples.

Conditional logistic regression analysis assuming an additive model was performed using PLINK to test for independence of association signals observed in neighbouring genes, or between

associated SNPs within the same gene. Tests for pairwise SNP interactions were performed using the epistasis command in PLINK. The combined analysis of the Swedish and US case-control data

was performed using the software Metal (http://www.sph.umich.edu/csg/abecasis/Metal/index.html). Pooled odds ratios were calculated using the Mantel–Haenszel method under a fixed effects

model, and tests for heterogeneity of odds ratios between studies were calculated using the MedCalc software (http://www.medcalc.be/). Power calculations were performed using the software

QUANTO (http://hydra.usc.edu/GxE/) assuming a log-additive model, and a prevalence for SLE in Sweden of 0.05%. RESULTS We selected a panel of SNPs in 78 genes with key functions related to

the type I IFN signalling system to study their association with SLE in a Swedish case-control cohort. The selected genes encode Toll-like receptors (TLRs) and intracellular sensor molecules

for nucleic acids (ie RIG-I-like receptors: RLR) and members of their signalling pathways, including several transcription factors that are active in the IFN producing pDCs and membrane

proteins of the pDCs. Genes encoding the members of the type I IFN family and other genes regulated by the TLRs that are involved in the response to the type I and type III IFNs, and genes

for which the expression is directly regulated by type I IFNs, were also included in the panel. Although the type I and type III IFNs bind two different receptors, the IFNAR and IFN-_λ_

receptor, they share downstream signalling and IFN-_λ_-induced genes are also induced by type I IFNs. A total of 14 additional genes that are not directly involved in the type I IFN system,

but have been suggested to be associated with SLE were also included (Supplementary Table S3). This analysis identified 21 SNPs in seven genes that yielded unadjusted _P_-values <0.01:

_IKBKE, TANK, STAT1, IL8, NRP1, TRAF6_ and _PIAS4_ (Figure 1 and Supplementary Table S3). At this significance level only nine associated SNPs would be expected to yield association signals

by chance, which indicates the presence of true association signals in our data (Supplementary Figure S1). The power for the discovery phase, which included 482 SLE cases and 536 controls,

was 65% to detect an OR of 1.5 at 0.01 significance for a 10% frequency allele. However, our power to detect genes with an OR of 1.2 was considerably lower (10%), and thus we cannot exclude

that genes, which remained undetected in our study may contribute to the risk for SLE. To increase power, we designed a panel of SNPs in the IKBKE, TANK, STAT1, IL8, NRP1, TRAF6 and PIAS4

genes for genotyping in an independent collection of Swedish SLE patients and controls. The _STAT5B_ gene was also included in the follow-up study, as initially one SNP in the gene showed a

_P_-value <0.01. This was, however, before an additional quality control step, by which related samples and population outliers were excluded. For genes, where multiple SNPs showed

_P_-values <0.05 in the discovery phase, candidate SNPs for follow-up were tested for independence of their association signal in relation to the most strongly associated SNP in each gene

(Supplementary Table S4). A partly redundant set of 21 SNPs that accounted for the association signals from the discovery phase was then analysed in the second Swedish case-control cohort.

Also in this confirmatory cohort genetic outliers were excluded. By combining the data from the Swedish discovery and confirmatory cohorts, totalling 826 cases and 1835 controls, we observed

strong association signals with _P_<5 × 10−4 for the SNPs rs2030171 in _STAT1_ and rs4694178 in _IL8_ (Table 1 and Supplementary Table S5). Multiple linked SNPs in the TRAF family

member-associated NF_κ_B activator (_TANK_) and TNF receptor-associated factor 6 (_TRAF6_) genes also gave suggestive signals of association with SLE in the combined Swedish cohort. In

addition, two weakly correlated SNPs in the _IKBKE_ gene (rs1539243 and rs17433930, LD _r_2=0.34) displayed _P_-values <0.05. Conditional regression analysis did not provide evidence for

more than one allele contributing to risk for SLE in genes with multiple associated SNPs (Supplementary Table S5), nor was there any evidence for epistatic interactions between SNPs at

different loci. We sought independent replication of our results by using data from a GWAS on SLE in European Americans.14 The SNPs, rs1539243 and rs17433930, in the _IKBKE_ gene showed

signals of association with SLE also in the US data (_P_=0.0028 and _P_=0.0021, respectively) (Table 2 and Supplementary Table S6). The SNP rs1539243 had been directly genotyped in the US

cohort, and for rs17433930 imputed genotypes were analysed. Combined analysis of the data from the Swedish and US cohorts revealed convincing association signals with SLE for these SNPs

(_P_meta=0.00026, OR=1.19, and _P_meta=0.00010, OR=1.33, for rs1539243 and rs17433930, respectively), a result which was significant also after Bonferroni correction (_P_meta_corr<0.01).

The two _IKBKE_ SNPs rs17433930 and rs1539243, which we found to be associated with SLE are located in the tenth intron and fourth exon of the gene, respectively, where rs1539243 is a

synonymous SNP in amino-acid residue 67 (Ile) of the IKK_ɛ_ kinase. Although the SNP rs4694178, located 3.3 kb downstream of the _IL8_ gene, had only a trend-wise significant _P_-value in

the US cohort compared with the more convincing association with SLE in the Swedish cohort (_P_US=0.064, _P_SWE=5 × 10−5), its association signal remained significant in the combined

analysis after Bonferroni correction (_P_meta=0.00040, OR=1.17, _P_meta_corr<0.01) (Table 2). This SNP was imputed in the US data (confidence=0.85), however, the directly genotyped SNP

rs9999446, which is strongly correlated with the SNP rs4694178 (_r_2=0.86) yielded a similar result (_P_=0.085) for association with SLE. For the SNP rs10199181 in the _STAT1_ gene, we

observed combined _P_-values <1 × 10−3. The _STAT1_ gene is located close to the _STAT4_ gene in a region of high LD on chromosome 2q32.2. _STAT4_ contains two linked SNPs, rs10181656 and

rs7582694, which are strongly associated with SLE,18 and conditional regression analysis of the data from the combined Swedish cohort indicates that the association signals from the _STAT1_

and _STAT4_ SNPs are not independent of each other (data not shown, remaining _P_conditional>0.3). DISCUSSION Our association study of genes from the type I IFN pathway and additional

candidate genes for SLE highlighted two genes, _IKBKE_ and _IL8,_ as potential risk factors for SLE. In addition, the genes _TRAF6_ and _TANK_ showed significant association with SLE in the

Swedish cohorts. Furthermore, _IRF5, TYK2, STAT4, IFIH1_, _IRAK1_, _IRF8_ and the _PHRF1/IRF7_ region have been reported by us elsewhere to be associated with SLE.1, 4, 18 Thus,

polymorphisms in multiple genes connected to the type I IFN signalling system are important for SLE disease susceptibility. _IKBKE_, the inhibitor of nuclear factor kappa-B kinase subunit

epsilon gene, encodes IKK_ɛ_, a kinase that together with the TANK-binding kinase (TBK1) has a role in the innate antiviral response. IKK_ɛ_ and TBK1 are activated when two intracellular RLR

helicases, encoded by the IFIH1 and DDX58 genes, recognise viral RNA in virus-infected cells (Figure 2). These kinases are also activated upon stimulation of endosomal TLR3 by double

stranded DNA, or cell membrane TLR4 by bacterial lipopolysaccharide (LPS). Together with TBK1, IKK_ɛ_ mediates phosphorylation of the transcription factors IRF3 and IRF7, which leads to

their activation and subsequent transcription of type I IFN and other inflammatory cytokines, but also activation of NF_κ_B has been reported.19, 20 The activation of IRF3 and IRF7 can be

inhibited by an ubiquitin-editing enzyme (A20), encoded by the TNFAIP3 gene. As also variation in _TNFAIP3_ and _IFIH1_ are associated with SLE,4, 21, 22 this further supports an important

role for the RLR pathway in the disease process. There is also evidence that IKK_ɛ_ can phosphorylate STAT1, and thus contribute to the type I IFN signalling through the IFNAR.23 The IKBKE

gene has recently been implicated in risk for rheumatoid arthritis (RA).24 The two polymorphisms with the most significant association with RA were tested in the discovery phase of our study

(rs2151222 and rs3748022 with _P_=0.084 and _P_=0.49 for association to SLE, respectively), however, these variants appear to be independent from the _IKBKE_ variants rs1539243 and

rs17433930 that we identified as risk alleles for SLE (_r_2<0.1 discovery phase). The conjecture that IKBKE has a role in arthritis is supported by data from an animal model. IKK_ɛ_

knockout mice have been shown to be less sensitive to induction of arthritis and exhibit less joint destruction than control mice.25 In a published GWAS on women with SLE26 the _IKBKE_ SNP

rs1539243 was tested, but no association was observed (dbGaP, http://www.ncbi.nlm.nih.gov/gap). The power of that study was, however, only 23% at the _P_=0.05 level to detect the association

we observe. The chemokine IL-8 has a wide range of pro-inflammatory effects, and its production can be triggered by immune complexes that also have the capacity to induce type I IFN

production.27 Recent data also suggests that IL-8 production in virus-infected cells is IFN dependant.28 SLE patients with renal29 or CNS involvement30 have elevated IL-8 levels in their

serum and cerebrospinal fluid, respectively, and serum IL-8 levels and disease activity correlate in SLE patients.31 As SLE disease flares are associated with increased IFN-_α_ production,6

these observations provide a link between the SLE disease process, IL-8 and the type I IFN system. Although we observed a significant association of _IL8_ with SLE in this study, there are

previous conflicting reports on the association between _IL8_ and SLE,26, 32, 33, 34 only two of which, a Spanish case-control study and a GWAS in women with SLE, having similar power to our

discovery phase. The power of these studies was around 50% at the 0.05 significance level to detect the effect for _IL8_ that we observe. The LD between the SNP rs2227306 tested in the

Spanish study and the SNP rs4694178 in our study is very high (_r_2=0.97 in the HapMap CEU population), but they do not observe any association with SLE for this SNP.34 In our study, the

association signal is mainly contributed by the Swedish cohort, which has a higher frequency of the risk allele than both the US and Spanish cohorts (control frequency of rs4694178 C:

Sweden=0.46, USA=0.41 and the linked allele rs2227306 T: Spain=0.41). In the women GWAS,26 a SNP perfectly correlated with _IL8_ rs4694178 (rs4694636, _r_2=1 HapMap CEU) was tested, and

showed an odds ratio suggestive of association with SLE (OR CI: 1.01–1.49, dbGaP). The modest power to detect an effect of this size, or genetic heterogeneity between populations could

explain these conflicting results. Although the _TANK_ and _TRAF6_ genes, which gave clear association signals (_P_<0.001) in the Swedish cohort, did not replicate in the US GWAS data,

these genes remain interesting candidates. TANK signals immediately upstream of IKK_ɛ_ in the TLR4- and IFIH1/DDX58-mediated activation of type I IFNs and inflammatory cytokines in response

to bacterial and viral stimuli, respectively (Figure 2). Association of _TANK_ with SLE would thus further support an important role for the RLR pathway in SLE. TRAF6 is a ubiquitin ligase

that mediates signal transduction from, for example, members of the TLR family leading to activation of NF_κ_B and IRFs. Polyubiquitination of IRF5 after its interaction with IRAK1 is

mediated by TRAF6, which enables IRF5 to translocate to the nucleus and exert its effect on gene expression. On the other hand, TNFAIP3 can inhibit TLR-induced activity of NF_κ_B by

de-ubiquitination of TRAF6.35 Interestingly, also _IRAK1_ has been associated with risk for SLE,36 and because SNPs in the _TRAF6_ region and in _TNFAIP3_ have also been associated with risk

for RA,37, 38, 39 it seems as variants of all these genes have the potential to contribute to loss of tolerance and autoimmune reactions. Further studies will be needed to determine whether

the TANK and TRAF6 genes have an effect on SLE, and whether this effect is specific for Scandinavian populations. Our study confirms the important role of the type I IFN system in SLE, and

suggests multiple genes from this pathway as candidates for functional studies and as interesting therapeutic targets (Figure 2). These results also point more specifically to the importance

of genes in the RLR pathway, which is activated in response to viral infections because of the ability of IFIH1/DDX58 to recognise cytoplasmic viral RNA. This pathway is active in cells

other than the pDCs, including monocyte derived dendritic cells. In addition to IFIH1, factors such as TANK, IKBKE and TNFAIP3 contribute to signalling in the RLR pathway (reviewed in 40).

However, there is also evidence for involvement in SLE of the MYD88-dependent pathway activated by endosomal TLR7/9 by RNA/DNA from dying cells, immune complexes (IC) or by viral RNA/DNA,

because _IRF8_, _IRAK1_, _FCGR2A_ and potentially _TRAF6,_ in this pathway are associated with SLE. Thus, at least two pathways seem important in SLE, both leading to production of type I

IFN and inflammatory cytokines through activation of IRF3, IRF5 and IRF7, and additional transcriptions factors, especially NF_κ_B. Association to SLE has further been demonstrated for the

type I IFN signalling through the IFNAR, specifically for _TYK2_ and _STAT4_, as well as the IFN-regulated genes _IFIH1_, _IRF5_, _IRF7_ and _IL8_. Consequently, a large number of genes,

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Download references ACKNOWLEDGEMENTS This study was supported by a Target Identification in Lupus (TIL) grant from the Alliance for Lupus Research, US, the Swedish Research Council for

Medicine, the Knut and Alice Wallenberg Foundation, the Swedish Rheumatism Foundation, the King Gustaf V 80-year Foundation, COMBINE, the European Community 6th Framework Program

(LSHM-CT-2007-037273), the Swedish Heart-Lung Foundation, the Torsten and Ragnar Söderberg Foundation, the ‘Visare Norr’ Fund for Northern County Councils of Sweden, The Åke Wiberg

Foundation, ALF funding from Stockholm County Council and Karolinska Institutet, the National Institutes of Health (R01 AR44804, K24 AR02175), the National Center for Research Resources (5

M01 RR00079), and a Kirkland Scholar Award to LAC. We thank Rezvan Kiani Dehkordi at the Rheumatology Clinic, Uppsala University Hospital, for assistance with DNA sample collection.

Professor Göran Hallmans, Head of the Medical Biobank of Northern Sweden for providing blood samples. Ann-Christin Wiman, Caisa Pöntinen, Molecular Medicine, Department of Medical Sciences,

Uppsala University, for assistance with genotyping. Genotyping was performed using equipment available at the SNP Technology Platform in Uppsala, Sweden (http://www.genotyping.se). AUTHOR

INFORMATION Author notes * Sophie Garnier Present address: 12Current address: INSERM UMR S937, Génétique Epidémiologique et Moléculaire des Pathologies Cardiovasculaires, Université Paris

VI, Paris, France., * Snaevar Sigurdsson Present address: 13Current address: Broad Institute of Harvard and MIT, Boston, MA, USA., AUTHORS AND AFFILIATIONS * Department of Medical Sciences,

Molecular Medicine, Uppsala University, Uppsala, Sweden Johanna K Sandling, Sophie Garnier, Snaevar Sigurdsson, Chuan Wang & Ann-Christine Syvänen * Department of Medical Sciences,

Section of Rheumatology, Uppsala University, Uppsala, Sweden Gunnel Nordmark, Maija-Leena Eloranta & Lars Rönnblom * Department of Medicine, Rheumatology Unit, Karolinska

Institutet/Karolinska University Hospital, Stockholm, Sweden Iva Gunnarsson, Elisabet Svenungsson & Leonid Padyukov * Department of Clinical Sciences, Section of Rheumatology, Lund

University, Lund, Sweden Gunnar Sturfelt, Andreas Jönsen & Anders A Bengtsson * Department of Laboratory Medicine, section of M.I.G., Lund University, Lund, Sweden Lennart Truedsson *

Department of Clinical Immunology, Umeå University Hospital, Ume, å, Sweden Catharina Eriksson * Department of Rheumatology, Umeå University Hospital, Umeå, Sweden Solbritt

Rantapää-Dahlqvist * Department of Medicine, Atherosclerosis Research Unit, Solna Karolinska Institutet Stockholm, Stockholm, Sweden Anders Mälarstig, Rona J Strawbridge & Anders Hamsten

* Department of Medicine, Rosalind Russell Medical Research Center for Arthritis, University of California, San Francisco, CA, USA Lindsey A Criswell * Genentech Inc., South San Francisco,

CA, USA Robert R Graham & Timothy W Behrens * Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden Gunnar Alm

Authors * Johanna K Sandling View author publications You can also search for this author inPubMed Google Scholar * Sophie Garnier View author publications You can also search for this

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THIS ARTICLE CITE THIS ARTICLE Sandling, J., Garnier, S., Sigurdsson, S. _et al._ A candidate gene study of the type I interferon pathway implicates _IKBKE_ and _IL8_ as risk loci for SLE.

_Eur J Hum Genet_ 19, 479–484 (2011). https://doi.org/10.1038/ejhg.2010.197 Download citation * Received: 05 May 2010 * Revised: 09 August 2010 * Accepted: 08 October 2010 * Published: 22

December 2010 * Issue Date: April 2011 * DOI: https://doi.org/10.1038/ejhg.2010.197 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get

shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * systemic

lupus erythematosus * type I interferon system * candidate gene study * single nucleotide polymorphism * IKBKE * IL8