In this study, we compared the association of several newly discovered susceptibility genes for systemic lupus erythematosus (SLE) between populations of European origin and two Asian populations. Using 910 SLE patients and 1440 healthy controls from Chinese living in Hong Kong, and 278 SLE patients and 383 controls in Thailand, we studied association of STAT4, BLK and PXK with the disease. Our data confirmed association of STAT4 (rs7574865, odds ratio (OR) =1.71, P=3.55 × 10−23) and BLK (rs13277113, OR=0.77, P=1.34 × 10−5) with SLE. It was showed that rs7574865 of STAT4 is also linked to hematologic disorders and potentially some other subphenotypes of the disease. More than one genetic variant in STAT4 were found to be associated with the disease independently in our populations (rs7601754, OR=0.59, P=1.39 × 10−9, and P=0.00034 when controlling the effect of rs7574865). With the same set of samples, however, our study did not detect any significant disease association for PXK, a risk factor for populations of European origin (rs6445975, joint P=0.36, OR=1.06, 95% confidence interval: 0.93–1.21). Our study indicates that some of the susceptibility genes for this disease may be population specific.
Systemic lupus erythematosus (SLE) is a complex disease with both genetic and environmental predisposing factors, and there are apparent population differences both in terms of disease prevalence and manifestations.1 Compared to Caucasians, for example, Asians have a higher disease prevalence (100 patients per 100 000 for women) and more renal involvement.2, 3, 4 Recent work on genome-wide association (GWA) studies has discovered several novel susceptibility genes for SLE, including STAT4, BLK, PXK, ITGAM, BANK1 and a few others.5, 6, 7, 8 However, these studies were mainly conducted on populations of European ancestry, and it is important to examine whether those genes are also risk factors for populations of other origins. Using 910 SLE patients and 1440 controls of Chinese ethnicity living in Hong Kong, as well as a case–control sample collection in Thailand, we examined some of the newly discovered susceptibility genes in our populations by genotyping the single nucleotide polymorphisms (SNPs) that showed the highest significance in association with the disease in the reported studies, but without high linkage disequilibrium (LD) to each other.
Remmers et al.5 reported association of STAT4 with disease risks in both rheumatoid arthritis (RA) and SLE. The haplotype marked by rs7574865 was found to be present on 31% of chromosomes of SLE patients but only on 22% of those in controls (odds ratio (OR)=1.55, P=1.87 × 10−9).5 This association was replicated by Hom et al.7 with 341 added cases and 2905 added controls from the study of Remmers et al. Association of STAT4 with SLE was also confirmed in several other studies.8, 9, 10 SNP rs7574865 was found to be associated with lupus nephritis, ds-DNA antibody production and age of onset.11, 12 In the GWA study by Hom et al.,7 rs7574865 in STAT4 showed highly significant association with SLE risk, with a P-value only second to variants in the human leukocyte antigen locus. In addition to rs7574865, both Harley et al.8 and Hom et al.7 showed that rs7601754 was also significantly associated with SLE. Although the P-values for this SNP were less significant than those found for rs7574865, the association was not readily explained by its LD with rs7574865, because the r2 value between the two is low in Caucasians according to HapMap data.
BLK is an src family tyrosine kinase involved in signal transduction downstream of B-cell receptor, and expression of BLK is highly restricted to B cells. The minor allele of rs13277113, an SNP located in the promoter region of BLK, was found to be associated with SLE in populations of European origin (OR=1.39, P=1 × 10−10). The risk allele was also found to be related with reduced expression of BLK and increased expression of C8orf13, a gene 25 kb away from this SNP on the opposite strand.7 Association of BLK with SLE was also confirmed by the study of Harley et al.8 on SNPs rs2248932 (OR=1.22, P=7 × 10−10) and rs10903340 (OR=1.18, P=1.46 × 10−7). For the latter study, association on SNP rs13277113 was not directly examined.
PXK is a Phox homology domain containing serine/threonine kinase with unknown function. The gene is located at chromosome 3p14.3, and seems to be expressed in a wide variety of tissues as reflected by the tissue origins of more than 300 expressed sequence tags for this gene (UniGene cluster: Hs.190544). SNP rs6445975 in intron 4 of PXK was found to be associated with SLE in all four sets of samples used in the study of Harley et al.,8 with P-values for all sets reaching statistical significance (P=0.04 to 1.84 × 10−5, joint P=7.01 × 10−9).
In this study, we examined association of these three susceptibility genes in the Chinese population living in Hong Kong and the Thai population living in Bangkok. Our results revealed both similarities and differences comparing to the findings from populations of European origin. We believe that population differences in the role of genetic factors involved in the disease may improve our understanding of the disease mechanisms and help improve clinical intervention of the disease.
We genotyped both rs7574865 and rs7601754 in STAT4 in our samples and found highly significant association of rs7574865 (OR=1.70, 95% confidence interval (CI): 1.51–1.92, P=3.58 × 10−18) and rs7601754 (OR=0.61, 95% CI: 0.50–0.73, P=2.12 × 10−7) with SLE. These results are completely replicated from the Thai samples (OR=1.75, 95% CI: 1.40–2.19, P=8.55 × 10−7; Table 1). Heterogeneity test on ORs from the two populations showed no significant difference (P>0.05 by Breslow–Day test on between-population OR heterogeneity as well as by partitioning the χ2-statistic between the two populations). The effects from the two SNPs do not seem to explain each other. The r2 value based on HapMap data as well as our own samples is between 0.067 and 0.084 between the two SNPs in both Caucasians and Chinese. Logistic regression as well as haplotype-based independence test using PLINK13 showed that both sites are associated with the disease risk independently, with a P-value of 0.00034 for rs7601754 association when controlling the effect of rs7574865. The result suggests that more than one functional variant in this gene locus may confer disease risk to SLE in our population, which is different from findings from Caucasians. Taylor et al.11 showed that four significantly associated SNPs in this locus are all highly linked. In their study, rs7601754 showed marginal significance when controlling the effect of rs7574865 (Table 4 in Taylor et al.11).
Taylor et al.11 have shown that rs7574865 was more strongly associated with SLE with double-stranded DNA antibody production, lupus nephritis and age at diagnosis. We have seen the same trend in our cohort for lupus nephritis, anti-ds-DNA antibody production and immunologic disorders. However, case-only tests in our study produced only significant difference for hematologic disorders and photosensitive (P=0.007 and 0.03, respectively; Table 2). Sample size could be the reason for the insignificance in some of the comparisons (see Supplementary Figure 3–4 for power calculation on subphenotype analysis).
We also examined association of BLK with SLE in our two Asian populations. We genotyped both rs13277113 and rs2248932 in BLK in Hong Kong samples in this study (we did not choose rs10903340 based on the much bigger P-value found in the reported study than for rs2248932). Our results replicated the findings from Caucasians on the association of rs13277113. Notably, the same risk allele (A) is the major allele in our population instead (OR=0.74 on the minor allele, 95% CI: 0.65–0.85, P=1.42 × 10−5). We also found significant association for rs2248932, an SNP located in the first intron of BLK, 43 kb downstream of rs13277113 with SLE risk (OR=0.84 on the minor allele, 95% CI: 0.71–0.99, P=0.034). However, the effect seems to be dependent on that of rs13277113 (P=0.25 in an independence test by logistic regression controlling the effect of rs13277113). The two SNPs have moderate LD to each other, with r2 equals 0.39 and 0.57 in Caucasians and Chinese, respectively. The strong association of rs13277113 in BLK with SLE in Chinese is not surprising, as the study by Hom et al.7 has shown that this SNP is associated with BLK expression in both Asians (Chinese and Japanese) and Caucasians. Stratification on subphenotypes on this gene did not show any significant differences (data not shown).
Although there is a similar enrichment of the risk allele for rs13277113 of BLK in the Thai SLE cases (allele ‘A’ increased from 67.6% in controls to 70.7% in cases), the association is not statistically significant (OR=0.86, 95% CI: 0.68–1.10, P=0.23; Table 1). However, the ORs from the Chinese and the Thai populations are not significantly different (P=0.27 by the Breslow–Day test for heterogeneity of ORs), with the joint OR=0.77 (95% CI: 0.68–0.87, P=1.22 × 10−5) by Cochran–Mantel–Haenszel (CMH) test (Table 1). The two populations did show significant difference on this site as determined by CMH test for difference for SNPs between populations given any possible SNP/disease association (P=0.0016). It seems that these two closely related populations differ at certain genomic regions in terms of allele frequencies (Table 1). The less than significant association in the Thai population probably reflected the smaller sample size comparing to that of the Hong Kong samples (see power calculation for Thai samples in Supplementary Figure 2).
PXK was recently reported to be associated with SLE in Caucasians in a robust analysis of GWA data.8 In our study, the frequency of the same allele (G) was virtually the same between the control group (18.55%) and SLE patients (19.26%), giving an OR of 1.05 (95% CI: 0.90–1.22, P=0.54; Table 1). We have also replicated our findings in SLE patients and controls from the Thai population, which showed similar allele frequency as Hong Kong Chinese and did not show any significant association with SLE (OR=1.12, 95% CI: 0.85–1.48, P=0.43; joint OR=1.06, 95% CI: 0.93–1.21, joint P=0.36; Table 1).
Different findings between populations in association studies could be caused by different functional variants between populations, or different LD pattern between markers and hidden functional variants. Analyzing HapMap data overlapping the PXK locus, we observed a single haplotype block for Han Chinese in Beijing (HCB), much different from that in the Caucasians (Figure 1). The two alleles of rs6445975 distinguish two major haplotypes in this region, which collectively explain more than 90% of the chromosomes defined by common variants in our population. Genotyping other known SNPs in this region according to HapMap data will only help distinguish haplotypes of very low allele frequencies (<3.6%).
It is also possible that the gene is associated with certain disease subphenotypes but not with overall susceptibility. Analysis on our patient samples did not show significant differences for this locus with any subphenotypes, although this could be due to the much reduced sample sizes for each subgroup based on certain phenotypes (Table 2; Supplementary Figure 3–4 for power of the study).
In this study we verified findings from populations of European origin and also pointed out some differences between European and Asian populations in SLE-associated genes. It is possible that undetected differences in population admixture or population substructure can cause spurious associations in case–control studies, or false negatives in certain situations. Although we cannot analyze this on a genome level, we have compared MAF for the SNPs genotyped in this study with those in HCB from HapMap, and found that data from the two sources are consistent with each other, although it is only based on a few SNPs and a small number of individuals in HapMap data. Our ongoing work on a genome-wide analysis seems to indicate that hidden population structure is unlikely to be a problem for association studies—when we use controls collected from Hong Kong.
It seems that there is a population difference for the role of PXK in SLE susceptibility. In association studies, a negative association could also be due to insufficient power of the studies. On the basis of our sample size, and a sex-average disease prevalence of 60 patients per 100 000 people in Chinese,2 assuming the same OR of 1.25 as in the reported study, we have a power of 0.88 with α=0.05 for a multiplicative model14 (Supplementary Figure 1). However, a note of caution is that our study is underpowered to detect an association of small effect size, such as the lower 95% CI for OR for this locus in the study of Harley et al., which is only 1.16. Further, we cannot rule out the possibility that the gene has an association with certain subphenotypes of the disease, for which our study has even less power (see Supplementary Figure 3–4). It emphasizes the importance of large sample size or meta-analysis of different studies to reveal associations of small effect sizes.
The STAT4 gene encodes a transcription factor mediating the effect of several cytokines, including IL12, the type I interferons and IL-23 in T cells and monocytes, leading to T-helper type 1 and type 17 differentiation, monocyte activation and interferon-γ production. STAT3 and STAT4 were shown to be constitutively activated in Crohn's patients but not in healthy volunteers.15 STAT4 has been shown to be involved in several autoimmune diseases, such as inflammatory bowel disease and type I diabetes mellitus16 as well as Sjogren's disease17 in addition to SLE and RA. Association of rs7574865 with SLE in multiple populations and with disease severity5, 9, 10, 11 indicates that the SNP may be a functional variant itself, but this cannot be proved unless there is detailed functional characterization of the SNP or extensive in-depth sequencing in the region excluding the existence of a true functional variant in LD with rs7574865.
Additive model seems to fit the association of rs7574865 of STAT4 suitably, a result consistent with published data in populations of European origin. Our sample produced higher OR than those in the reported results (joint OR of 1.71 from Hong Kong and Thai samples, vs 1.55 in the earlier report5). Interestingly, higher ORs were reported in samples of European origin from patients with severe disease manifestations for this gene.11, 12 The higher OR found in our Asian populations compared to those in Caucasians on rs7574865 may be a reflection of the disease severity in Asians. Our data on the subphenotype stratification are largely consistent with the findings by Taylor et al.,11 which we believe, with increased sample size, may provide further evidence on the stronger association of rs7574865 with severe phenotypes of the disease, such as hematologic disorder, nephritis and ds-DNA antibody production. Recently, Kawasaki et al.18 showed that rs7574865 has higher ORs with SLE patients with nephritis, anti-ds-DNA antibody production and early onset age, although none reached statistical significance, presumably due to small sample size in their study (308 cases vs 306 controls). A word of caution is that subphenotype stratification opens the door for false positives due to multiple testing, which could be overcome by comparing results from different studies, and examining the comprehensive pattern of subphenotype association.
The independent contribution of rs7601754 toward the disease susceptibility seems to be also different from findings from Caucasians, an area that warrants further investigation. The study of Taylor et al. reported marginal P-values for rs7601754 in disease association when controlling the effect of rs7574865 (Table 4 in Taylor et al.11), and concluded that there is no compelling evidence for additional risk alleles other than rs7574865 in this gene. In the study of Harley et al., the risk allele (T allele) of rs7601754 increased from 81.3% from controls to 86.6% in female SLE patients of European ancestry, with a P-value of 3.7 × 10−6 (Table 4 in Harley et al.8). Considering the low LD between rs7574865 and rs7601754, their data may indicate an independent contribution from rs7601754, although independence test was not mentioned from the study. Findings from an SLE cohort in the Japanese population18 also showed a 5% enrichment of the ‘T’ allele in diseased group, similar to our findings from Hong Kong Chinese and Thai. All the evidence considered, it seems that rs7601754 probably represents an independent variant associated with SLE. We think that there may be an effect size difference for this SNP between the two populations (0.59 for Hong Kong and Thai found in this study, and >0.71 in Caucasians), which may explain the less significant independent effect for rs7601754 in the study of Taylor et al.
It is apparent that certain genetic risk factors may be important only in certain populations but not in others. For example, a variant in the inhibitory receptor FCGRIIB gene was found to have increased frequency in SLE patients of African and Asian populations, but not in patients of European origin.19 Recently, it has been found that low copy number variation of FCGRIIIB confers SLE susceptibility to patients of European origin but not to Hong Kong Chinese.20 A major allele being a risk allele in the case of BLK is not surprising, but it may mean that the allele poses more risk to Asians on the population level. Because Asians have higher disease prevalence and more severe disease manifestations than Caucasians, it is likely that Asians may have higher genetic load than Caucasians in terms of susceptibility to the disease. The negative findings on SLE association on PXK in Asian populations may indicate that Asians may have other susceptibility genes associated with the disease.
With GWA studies beginning to bear fruits, many susceptibility genes for complex diseases such as SLE are being uncovered with an unseen pace. Determining population differences, identifying functional variant(s), and exploring the relationship of genetic background with disease manifestations and potential benefits of genetic testing for clinical intervention are the important follow-up steps. Understanding of population differences in genetic susceptibility for a complex disease like SLE could surely help us improve our understanding of the disease mechanisms and improve clinical intervention of the disease accordingly.
Patients and methods
All the SLE patients were recruited from three Hong Kong hospitals: Queen Mary Hospital, Tuen Mun Hospital and Pamela Youde Nethersole Eastern Hospital. Medical records were reviewed to confirm that subjects met the criteria of the American College of Rheumatology for SLE diagnosis. The patients were all self-reported Chinese ethnicity living in Hong Kong. These included 836 women and 74 men with a mean age of 44.6 years. The study was approved by the institutional review board of the University of Hong Kong and Hospital Authority, Hong Kong West Cluster, New Territory West Cluster and Hong Kong East Cluster, and all patients gave informed consent. Renal involvement was defined by proteinuria>0.5 g per day or biopsy-proven lupus nephritis. Hematologic disorders included leukopenia, lymphopenia, thrombocytopenia and/or hemolytic anemia. Detailed clinical records are available for 735 patients from our collection that were used in this study. A total of 1440 Hong Kong Chinese blood donors from Hong Kong Red Cross were recruited as controls. These included 519 women and 918 men with a mean age of 29.6 years. They are also self-reported to be of Chinese ethnicity.
A total of 278 Thai patients with SLE (female/male ratio=260:18; mean age 35.6 years) attending King Chulalongkorn Memorial Hospital, a tertiary referral center in Bangkok, who fulfilled at least four of the American College of Rheumatology 1982 revised criteria for SLE, were included in this study. A total of 383 Thai normal control subjects (female/male ratio=331:52; mean age 35.8 years) were recruited from unrelated voluntary healthy donors from the same ethnic background and geographic area. The study was approved by the ethics committee of the King Chulalongkorn University and all the subjects gave informed consent.21
SNP rs7574865, rs7601754, rs13277113, rs2248932 and rs6445975 were genotyped by TaqMan method using either Assay-on-Demand or Assay-by-Design probes and primers (catalogue nos. C_29882391_10 for rs7574865, C_11515729_10 for rs7601754, C_309500_10 for rs6445975, C_1886916_10 for rs13277113 and C_1886848 for rs2248932; Applied Biosystems, Foster City, CA, USA). Genotyping accuracy was confirmed by direct sequencing of PCR products for some randomly chosen samples.
All SNPs were tested for significant deviation from Hardy–Weinberg equilibrium in controls and all passed the test with P-values >0.05. The SNPs were analyzed for an association with the disease by means of comparison of the minor allele frequency in patients and controls (basic allelic test) as well as other tests using PLINK13 (genotype test of 3 × 2 contingency tables, Cochran–Armitage trend test, test of dominant and recessive models). LD patterns were analyzed and displayed by Haploview.22 Association of the SNPs with disease risk was also corrected by logistic regression using age and sex as covariates and the associations found in this study remain significant after all the corrections.
Average ORs and P-values jointly analyzed from both Hong Kong Chinese and Thai population were obtained by CMH test of association conditional on SNP differences between the two populations. Potential heterogeneity of ORs for a given SNP between the two populations was tested by both Breslow–Day test and by partitioning the χ2-statistic between the two populations. Test of independent contribution of an SNP controlling for the effect of other SNPs in the same gene was done by logistic regression. Association with subphenotype was analyzed by comparing cases with a certain subphenotype with controls, cases without the subphenotype with controls, heterogeneity test of two ORs derived this way and direct comparison of the cases with and without the subphenotype.
Danchenko N, Satia JA, Anthony MS . Epidemiology of systemic lupus erythematosus: a comparison of worldwide disease burden. Lupus 2006; 15: 308–318.
Mok CC, Lau CS . Lupus in Hong Kong Chinese. Lupus 2003; 12: 717–722.
Mok CC, Tang SS . Incidence and predictors of renal disease in Chinese patients with systemic lupus erythematosus. Am J Med 2004; 117: 791–795.
Seligman VA, Lum RF, Olson JL, Li H, Criswell LA . Demographic differences in the development of lupus nephritis: a retrospective analysis. Am J Med 2002; 112: 726–729.
Remmers EF, Plenge RM, Lee AT, Graham RR, Hom G, Behrens TW et al. STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus. N Engl J Med 2007; 357: 977–986.
Nath SK, Han S, Kim-Howard X, Kelly JA, Viswanathan P, Gilkeson GS et al. A nonsynonymous functional variant in integrin-alpha(M) (encoded by ITGAM) is associated with systemic lupus erythematosus. Nat Genet 2008; 40: 152–154.
Hom G, Graham RR, Modrek B, Taylor KE, Ortmann W, Garnier S et al. Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX. N Engl J Med 2008; 358: 900–909.
Harley JB, Alarcon-Riquelme ME, Criswell LA, Jacob CO, Kimberly RP, Moser KL et al. Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci. Nat Genet 2008; 40: 204–210.
Kobayashi S, Ikari K, Kaneko H, Kochi Y, Yamamoto K, Shimane K et al. Association of STAT4 with susceptibility to rheumatoid arthritis and systemic lupus erythematosus in the Japanese population. Arthritis Rheum 2008; 58: 1940–1946.
Palomino-Morales RJ, Rojas-Villarraga A, Gonzalez CI, Ramirez G, Anaya JM, Martin J . STAT4 but not TRAF1/C5 variants influence the risk of developing rheumatoid arthritis and systemic lupus erythematosus in Colombians. Genes Immun 2008; 9: 379–382.
Taylor KE, Remmers EF, Lee AT, Ortmann WA, Plenge RM, Tian C et al. Specificity of the STAT4 genetic association for severe disease manifestations of systemic lupus erythematosus. PLoS Genet 2008; 4: e1000084.
Sigurdsson S, Nordmark G, Garnier S, Grundberg E, Kwan T, Nilsson O et al. A common STAT4 risk haplotype for systemic lupus erythematosus is over-expressed, correlates with anti-dsDNA production and shows additive effects with two IRF5 risk alleles. Hum Mol Genet 2008; 17: 2868–2876.
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559–575.
Skol AD, Scott LJ, Abecasis GR, Boehnke M . Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet 2006; 38: 209–213.
Lovato P, Brender C, Agnholt J, Kelsen J, Kaltoft K, Svejgaard A et al. Constitutive STAT3 activation in intestinal T cells from patients with Crohn's disease. J Biol Chem 2003; 278: 16777–16781.
Martinez A, Varade J, Marquez A, Cenit MC, Espino L, Perdigones N et al. Association of the STAT4 gene with increased susceptibility for some immune-mediated diseases. Arthritis Rheum 2008; 58: 2598–2602.
Korman BD, Alba MI, Le JM, Alevizos I, Smith JA, Nikolov NP et al. Variant form of STAT4 is associated with primary Sjogren's syndrome. Genes Immun 2008; 9: 267–270.
Kawasaki A, Ito I, Hikami K, Ohashi J, Hayashi T, Goto D et al. Role of STAT4 polymorphisms in systemic lupus erythematosus in a Japanese population: a case–control association study of the STAT1–STAT4 region. Arthritis Res Ther 2008; 10: R113.
Clatworthy MR, Willcocks L, Urban B, Langhorne J, Williams TN, Peshu N et al. Systemic lupus erythematosus-associated defects in the inhibitory receptor FcgammaRIIb reduce susceptibility to malaria. Proc Natl Acad Sci USA 2007; 104: 7169–7174.
Willcocks LC, Lyons PA, Clatworthy MR, Robinson JI, Yang W, Newland SA et al. Copy number of FCGR3B, which is associated with systemic lupus erythematosus, correlates with protein expression and immune complex uptake. J Exp Med 2008; 205: 1573–1582.
Hirankarn N, Avihingsanon Y, Wongpiyabovorn J . Genetic susceptibility to SLE is associated with TNF-alpha gene polymorphism −863, but not −308 and −238, in Thai population. Int J Immunogenet 2007; 34: 425–430.
Barrett JC, Fry B, Maller J, Daly MJ . Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005; 21: 263–265.
This study was partially supported by the Shun Tak District Min Yuen Tong of Hong Kong. PN and MZ were supported by Edward Sai Kim Hotung Paediatric Education and Research Fund, and University Postgraduate Studentship. WY acknowledges support from UGC, UHK (200711159155).
About this article
Cite this article
Yang, W., Ng, P., Zhao, M. et al. Population differences in SLE susceptibility genes: STAT4 and BLK, but not PXK, are associated with systemic lupus erythematosus in Hong Kong Chinese. Genes Immun 10, 219–226 (2009). https://doi.org/10.1038/gene.2009.1
- systemic lupus erythematosus
- population difference
Validation of genome-wide associated variants for Kawasaki disease in a Taiwanese case–control sample
Scientific Reports (2020)
The association of the UHRF1BP1 gene with systemic lupus erythematosus was replicated in a Han Chinese population from mainland China
Annals of Human Genetics (2020)
A review of advances in the understanding of lupus nephritis pathogenesis as a basis for emerging therapies
Independent Replication on Genome-Wide Association Study Signals Identifies IRF3 as a Novel Locus for Systemic Lupus Erythematosus
Frontiers in Genetics (2020)
Association of STAT4 Gene Rs7574865, Rs10168266 Polymorphisms and Systemic Lupus Erythematosus Susceptibility: A Meta-analysis
Immunological Investigations (2020)