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Abstract
Background/Purpose SLE (Systemic Lupus Erythematosus) and SjD (Sjögren’s Disease) are similar diseases. Patients with these conditions share many overlapping features and some patients meet the classification criteria for both disease states. These patients form a subset of SLE with secondary SjD. Further, both diseases share clinical and serologic features. similar serological profiles, notably. This overlap includes: anti-Ro/SSA and anti-La/SSB positivity, skin lesions, xerostomia, xerophthalmia, association with neonatal lupus syndrome, primary biliary cirrhosis, autoimmune thyroid disease, female predominance and similar cancer risk distribution. Together, this suggests shared pathobiologic and etiologic mechanisms. Molecular profiling has implicated aberrant IFN signalling in both diseases. Both diseases arise from interaction of polygenic genetic risk factors and environmental exposures. Shared genetic risk is a potential explanation for. Both diseases show familial aggregation, with a familial history of either increasing the risk for both diseases. GWAS studies have identified similar genomic risk regions. Given overlapping clinical features and pathobiologic mechanisms, we asked:
Are the causal genetic risk factors for SLE and SjD shared?
Methods We compared the causal genetic risk for SLE and SjD using three complementary approaches. First, we examined published GWAS results for these two diseases by analysing the predicted causal gene protein-protein interaction networks of both diseases. Since method does not account for overlapping risk intervals, we also examined whether such intervals overlap between these two diseases. Third, we used two-sample GWAS summary statistic- based Mendelian randomization (two-sample MR) to determine whether risk variants for SLE are causal for SjD and vice versa.
Results We found that both the putative causal genes and the genomic risk intervals for SLE and SjD overlap much more than would be expected by chance (figure 1, table 1). Further, two sample MR analysis confirmed that alone or in aggregate, SLE is likely causal 31 for SjD and vice versa. [SjD variants predicting SLE: OR=2.56; 95% CI (1.98–3.30); P < 1.4E-13, inverse variance weighted; SLE variants predicting SjD: OR=1.36; 95% CI (1.26–1.47); P < 1.6 E-11, inverse variance weighted].
Conclusion Overlapping causal genetic risk factors were found for both diseases using complementary approaches. Our observations support the hypothesis that these genetic factors drive the same pathobiologic mechanisms. These shared pathways may explain the similar presentation and overlap of both diseases. Our work has important implications for differential diagnosis of these two conditions. It is perhaps more parsimonious to consider SjD a form fruste of SLE or to consider SLE a severe form of SjD. It also highlights the potential to accelerate our understanding of SjD genetics by analysing the shared genetic basis for these two conditions. By doing so, we might be able increase the statistical power to detect genetic association in SjD (where the genetic risk is less completely defined).
SjD and SLE GWAS risk overlaps significantly. Overrepresentation analysis comparing predicted causal gene protein-protein interaction networks and GWAS identified association intervals for Sjögren’s Disease (SjD) and Systemic Lupus Erythematosus (SLE)
Overlap between SjD and SLE predicted causal genes. Overlap of predicted-protein interactions from STRING are shown for causal genes identified by the Open Targets Genetics locus 2 gene (L2G) algorithm or our annotation
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