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ObjectiveSystemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations.MethodsWe newly genotyped 10 029 SLE cases and 180 167 controls and subsequently meta-analysed them jointly with 3348 SLE cases and 14 826 controls from published studies in East Asians. We further applied a Bayesian statistical approach to localise the putative causal variants for SLE associations.ResultsWe identified 113 genetic regions including 46 novel loci at genome-wide significance (p<5×10−8). Conditional analysis detected 233 association signals within these loci, which suggest widespread allelic heterogeneity. We detected genome-wide associations at six new missense variants. Bayesian statistical fine-mapping analysis prioritised the putative causal variants to a small set of variants (95% credible set size ≤10) for 28 association signals. We identified 110 putative causal variants with posterior probabilities ≥0.1 for 57 SLE loci, among which we prioritised 10 most likely putative causal variants (posterior probability ≥0.8). Linkage disequilibrium score regression detected genetic correlations for SLE with albumin/globulin ratio (rg=−0.242) and non-albumin protein (rg=0.238).ConclusionThis study reiterates the power of large-scale genome-wide meta-analysis for novel genetic discovery. These findings shed light on genetic and biological understandings of SLE.

Despite increasing evidence that long non-coding RNAs (lncRNAs) widely take part in human diseases, the role of lncRNAs in systemic lupus erythematosus (SLE) is largely unknown. In this study, we performed a two-stage study to explore the plasma levels of five lncRNAs (GAS5, linc0949, linc0597, HOTAIRM1 and lnc-DC) and their potential as SLE biomarkers. Compared with healthy controls, plasma levels of GAS5 and lnc-DC were significantly decreased (P < 0.001 and P = 0.002, respectively) while linc0597 were overexpressed in SLE patients (P < 0.001). When SLE patients were divided into SLE without nephritis and lupus nephritis (LN), the levels of lnc-DC were significantly higher in LN compared with SLE without nephritis (P = 0.018), but no significant difference in levels of GAS5 and linc0597 were found between LN and SLE without nephritis; plasma linc0949 level showed no significant difference in all comparisons. Further evaluation on potential biomarkers showed that GAS5, linc0597 and lnc-DC may specifically identify patients with SLE, the combination of GAS5 and linc0597 provided better diagnostic accuracy; lnc-DC may discriminate LN from SLE without nephritis. In summary, GAS5, linc0597 and lnc-DC in plasma could be potential biomarkers for SLE.

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