The clustering of multiple autoimmune disorders in families and evidence for autoimmune pleiotropic loci are well known. Nevertheless, no comprehensive assessment of the specific shared variants between SLE and other autoimmune diseases (ADs) has yet been performed in a single large-scale study based on GWAS data. Analyses of shared SLE loci have been limited to specific loci and few diseases (reviewed in 
). In this study we used findings from published GWAS to assess the extent of genetic overlap between SLE and seventeen autoimmune diseases, testing if variants implicated in other ADs show association in our large SLE cohort. Given that the MHC is unquestionably a universal risk region for autoimmunity, and some GWAS did not report their results in this region, we excluded HLA loci from our analyses.
The loci that were associated with the largest number of ADs include IL23R
, and IL2RA
, supporting an important role for T cell and innate immune response pathways in autoimmunity. Nevertheless, these loci are not implicated in all ADs, suggesting that, with the exception of the HLA region, there seem to be no universal genetic risk factors for autoimmunity. It is commonly accepted that there is a common genetic background predisposing to autoimmunity and inflammation, and that further combinations of more disease-specific variation at HLA and non-HLA genes, in interaction with epigenetic and environmental factors, contribute to disease and its clinical manifestations 
. Our data additionally suggests that, instead of resulting from common risk factors, autoimmunity may result from specific and multiple different pleiotropic effects. This is consistent with a recent report showing that genomic pleiotropy is relatively low, as most genes affect only a small number of traits 
. The authors suggest that genes displaying a high degree of pleiotropy also exhibit an individually larger effect on each trait 
. It is likely that different population genetic factors (e.g., natural selection, migration/isolation, random mutation) in similar or distinct environments led to the establishment of different autoimmune loci and subsequent migrations and interbreeding have led to the current plethora of loci that predispose to autoimmunity.
Based on our analyses of shared non-HLA loci across ADs, the most genetically similar diseases appear to be CD with UC, and T1D with RA, sharing 15 and 11 loci, respectively. While the former pair is clearly supported by overlapping clinical manifestations, since both CD and UC are subsets of IBD, the overlap between the latter pair is not entirely clear based on their organ involvement. The clustering patterns do not seem biased by the number of reported loci for each disease. As such, while the genetic overlap between CD and UC may reflect the prevalence of more specific IBD genes, the genetic overlap between T1D and RA may reflect the existence of general, nonspecific autoimmunity genes.
Despite being a prototypic AD, the non-HLA genetic overlap between SLE and the ADs herein investigated is more modest than we anticipated. The disease with which it shares the most loci is RA, which is potentially interesting due to the common clinical presentation of arthritis. The number of reported SLE loci is similar to other ADs and does not explain its relative distance from other ADs. The clinical heterogeneity of SLE may, at least in part, account for the relatively modest number of shared loci. Different SLE loci are likely differentially associated with specific clinical criteria, as was recently shown in GWAS of anti-RNA binding proteins 
, and anti–dsDNA autoantibody production 
in SLE. It should also be noted that SLE may share more loci with systemic diseases not included or not well represented in our analyses. Our data included 49 loci reported for RA, two for BeD, three for SScl, but Sjögren's syndrome and antiphospholipid syndrome lack GWAS. Interestingly, two of the three loci reported in the GWAS of SScl, IRF5
, also show association in GWAS of SLE. Similarly, Anaya et al. 
recently analyzed the association of the SLE predisposing risk variant (rs1143679) for ITGAM-ITGAX
across 7 other ADs, only showing a suggestive association for SScl. For many of the shared GWAS autoimmune loci we found no evidence for association with SLE, including for IL23R
, in spite of having enough power to detect the effects reported in other diseases. Although we cannot exclude the possibility that 1) other variants in these loci predispose to SLE, or 2) that these loci have weaker effects in SLE implying a potential lack of statistical power, or 3) that their effects are conditional on other unknown loci, it is plausible that the lack of these common genetic factors contributes to SLE being a distinct disease. Also, several established SLE loci are apparently not associated with other ADs, including the ITGAM-ITGAX
regions. Obviously, these risk variants may simply have weaker effects in other ADs and the studies lacked power to detect them. This situation was recently illustrated in a meta-analysis of CD and CelD, where the increased power of the combined datasets allowed the detection of shared loci with a relatively small effect, hence undetectable in the individual diseases 
Our analyses identify novel shared SLE loci. The results that we report were adjusted for the number of comparisons, which decreases the likelihood of a false positive result. The V-set domain containing T cell activation inhibitor 1
) region, which has been reported in a GWAS of JIA, showed the strongest novel association with SLE. Evidence suggests that this gene plays a role in the negative regulation of T cell responses. The zinc finger ZGPAT
region also shows a significant association with SLE. Despite being clearly strong candidates because of their association with other ADs, the new SLE loci require validation. It is worth noting that we discovered associations consistent with and in contrast to the same risk allele in other ADs. This observation was recently confirmed by Wang et al. 
, who suggests that susceptibility loci involved in the pathogenesis of ADs may have antagonistic pleiotropic effects, where risk alleles for one disease may confer selective advantage for another disease or infection resistance. Given that the functional variant is not known, we cannot rule out that the inverse association arises from different LD patterns.
A limitation of our study is the fact that we restricted our analyses to variants reported from GWAS in populations of European Ancestry. Although we have certainly missed shared variants identified in large candidate gene studies or targeted meta-analyses, many ADs lack such studies. Thus, given the increasing coverage of the genome with modern SNP chips, we preferred to restrict our analyses to a directly comparable set of results based on GWAS. These agnostic scans help to minimize the extent of potential methodological and publication biases. We should note that our analyses do not provide an unbiased estimate of the total degree of genetic overlap amongst ADs, given that the application of stringent significance thresholds in GWAS certainly overlooks true risk loci. Future studies using all variants in these GWAS will be required to directly estimate the degree of shared susceptibility. Finally, it is important to note that some of the genetic overlap with SLE may have been missed in our analyses because a large proportion of candidate SNPs failed our quality control thresholds, and thus could not be effectively tested for association in our samples.
Much remains to be done before the genetic etiology of the autoimmunity spectrum is resolved. Continued studies of populations beyond those of European ancestry are certainly needed. A catalog of all shared and distinct risk loci requires that these regions be thoroughly resequenced in suitably large population samples, with additional genotyping of the resulting comprehensive set of variants in order to confirm and fully characterize the extent of genetic risk. The examination of the patterns observed here generates an appreciation for potential interplay between population genetic factors (e.g., natural selection, migration) and environmental factors and calls for the interrogation of these loci in significant numbers of samples from different ethnic populations.
This study represents the most comprehensive evaluation of shared autoimmune loci to date. In addition, we provide further evidence for previously and newly identified pleiotropic genes in SLE. These findings support a relatively distinct genetic susceptibility for SLE, a genetic basis for the shared pathogenesis of ADs, and the value of studies of potentially pleiotropic genes in autoimmune diseases.