Timothy Vyse, Yong Cui, Wanling Yang and colleagues report a meta-analysis of genome-wide association studies for systemic lupus erythematosus (SLE) including European and Chinese individuals. They identify ten new loci associated with SLE and find evidence for increased genetic risk of disease among individuals of non-European ancestry. Systemic lupus erythematosus (SLE; OMIM 152700) is a genetically complex autoimmune disease. Genome-wide association studies (GWASs) have identified more than 50 loci as robustly associated with the disease in single ancestries, but genome-wide transancestral studies have not been conducted. We combined three GWAS data sets from Chinese (1,659 cases and 3,398 controls) and European (4,036 cases and 6,959 controls) populations. A meta-analysis of these studies showed that over half of the published SLE genetic associations are present in both populations. A replication study in Chinese (3,043 cases and 5,074 controls) and European (2,643 cases and 9,032 controls) subjects found ten previously unreported SLE loci. Our study provides further evidence that the majority of genetic risk polymorphisms for SLE are contained within the same regions across both populations. Furthermore, a comparison of risk allele frequencies and genetic risk scores suggested that the increased prevalence of SLE in non-Europeans (including Asians) has a genetic basis.

Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underlie the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertake a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture are identified. In addition to the human leukocyte antigen (HLA) region, nine disease loci show clear ancestral differences and implicate antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores perform significantly better when trained on ancestry-matched data sets. These analyses help to reveal the genetic basis for disparities in SLE among ancestral groups.

Objective Systemic 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. Methods We 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. Results We 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 (r_g=−0.242) and non-albumin protein (r_g=0.238). Conclusion This 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.

Ferroptosis in tubules has been implicated in the pathogenesis of acute kidney injury (AKI), whereas the regulatory mechanism remains unclear. The stimulator of interferon genes (STING) is previously recognized as a critical mediator of innate immunity via a DNA-sensing pathway and has been increasingly linked to lipid peroxidation, a hallmark of ferroptosis. Herein we investigated the role and the underlying mechanism of STING in AKI models established by ischemia/reperfusion (IR) in C57BL mice. The expression level of STING was predominantly increased in tubules of kidney after IR treatment. Besides, STING deficiency markedly alleviated IR-induced lipid peroxidation, tissue damage and renal dysfunction. Consistently, in vitro experiments demonstrated that the increase in ferroptotic cell death, lipid ROS production and the decrease in GSH peroxidase 4 (GPX4) expression in renal tubular cells subjected to ferroptosis agonist or hypoxia/reoxygenation intervention were all mitigated by genetic deficiency or pharmacological inhibition of STING, while all exacerbated by STING overexpression. Further, these detrimental effects of STING overexpression relied on the induction of ferritinophagy, i.e. autophagic degradation of ferritin, leading to iron overload. Mechanistically, STING mediated the initiation of ferritinophagy through interacting with nuclear receptor coactivator 4 (NCOA4), a fundamental receptor for the transfer of ferritin into lysosome. Collectively, STING contributes to ferroptosis during ischemic AKI through facilitating NCOA4-mediated ferritinophagy and shows the potential as a promising therapeutic choice for AKI.

Using three European and two Chinese genome-wide association studies (GWAS), we investigated the performance of genetic risk scores (GRSs) for predicting the susceptibility and severity of systemic lupus erythematosus (SLE), using renal disease as a proxy for severity. We used four GWASs to test the performance of GRS both cross validating within the European population and between European and Chinese populations. The performance of GRS in SLE risk prediction was evaluated by receiver operating characteristic (ROC) curves. We then analyzed the polygenic nature of SLE statistically. We also partitioned patients according to their age-of-onset and evaluated the predictability of GRS in disease severity in each age group. We found consistently that the best GRS in the prediction of SLE used SNPs associated at the level of P < 1e−05 in all GWAS data sets and that SNPs with P-values above 0.2 were inflated for SLE true positive signals. The GRS results in an area under the ROC curve ranging between 0.64 and 0.72, within European and between the European and Chinese populations. We further showed a significant positive correlation between a GRS and renal disease in two independent European GWAS (Pcohort1 = 2.44e−08; Pcohort2 = 0.00205) and a significant negative correlation with age of SLE onset (Pcohort1 = 1.76e−12; Pcohort2 = 0.00384). We found that the GRS performed better in the prediction of renal disease in the ‘later onset’ compared with the ‘earlier onset’ group. The GRS predicts SLE in both European and Chinese populations and correlates with poorer prognostic factors: young age-of-onset and lupus nephritis.