Genetic variants in systemic lupus erythematosus susceptibility loci, XKR6 and GLT1D1 are associated with childhood-onset SLE in a Korean cohort

Prediction of systemic lupus erythematosus-related genes based on graph attention network and deep neural network

Systemic lupus erythematosus (SLE) is an autoimmune disorder intricately linked to genetic factors, with numerous approaches having identified genes linked to its development, diagnosis and prognosis. Despite genome-wide association analysis and gene knockout experiments confirming some genes associated with SLE, there are still numerous potential genes yet to be discovered. The search for relevant genes through biological experiments entails significant financial and human resources. With the advancement of computational technologies like deep learning, we aim to identify SLE-related genes through deep learning methods, thereby narrowing down the scope for biological experimentation. This study introduces SLEDL, a deep learning-based approach that leverages DNN and graph neural networks to effectively identify SLE-related genes by capturing relevant features in the gene interaction network. The above steps transform the identification of SLE related genes into a binary classification problem, ultimately solved through a fully connected layer. The results demonstrate the superiority of SLEDL, achieving higher AUC (0.7274) and AUPR (0.7599), further validated through case studies.

Association of endometriosis with Sjögren's syndrome: Genetic insights (Review)

Patients with a history of endometriosis have an increased risk of developing various autoimmune diseases such as rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, multiple sclerosis and celiac disease. There is a potential association between endometriosis and an increased susceptibility for Sjögren's syndrome (SS). SS is a common chronic, inflammatory, systemic, autoimmune, multifactorial disease of complex pathology, with genetic, epigenetic and environmental factors contributing to the development of this condition. It occurs in 0.5‑1% of the population, is characterized by the presence of ocular dryness, lymphocytic infiltrations and contributes to neurological, gastrointestinal, vascular and dermatological manifestations. Endometriosis is an inflammatory, estrogen‑dependent, multifactorial, heterogeneous gynecological disease, affecting ≤10% of reproductive‑age women. It is characterized by the occurrence of endometrial tissue outside the uterine cavity, mainly in the pelvic cavity, and is associated with pelvic pain, dysmenorrhea, deep dyspareunia and either subfertility or infertility. It is still unclear whether SS appears as a secondary response to endometriosis, or it is developed due to any potential shared mechanisms of these conditions. The aim of the present review was to explore further the biological basis only of the co‑occurrence of these disorders but not their association at clinical basis, focusing on the analysis of the partially shared genetic background between endometriosis and SS, and the clarification of the possible similarities in the underlying pathogenetic mechanisms and the relevant molecular pathways.

A Non-Coding Variant in SLC15A4 Modulates Enhancer Activity and Lysosomal Deacidification Linked to Lupus Susceptibility

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a strong genetic basis. Despite the identification of several single nucleotide polymorphisms (SNPs) near the SLC15A4 gene that are significantly associated with SLE across multiple populations, specific causal SNP(s) and molecular mechanisms responsible for disease susceptibility are unknown. To address this gap, we employed bioinformatics, expression quantitative trait loci (eQTLs), and 3D chromatin interaction analysis to nominate a likely functional variant, rs35907548, in an active intronic enhancer of SLC15A4. Through luciferase reporter assays followed by chromatin immunoprecipitation (ChIP)-qPCR, we observed significant allele-specific enhancer effects of rs35907548 in diverse cell lines. The rs35907548 risk allele T is associated with increased regulatory activity and target gene expression, as shown by eQTLs and chromosome conformation capture (3C)-qPCR. The latter revealed long-range chromatin interactions between the rs35907548 enhancer and the promoters of SLC15A4, GLTLD1, and an uncharacterized lncRNA. The enhancer-promoter interactions and expression effects were validated by CRISPR/Cas9 knock-out (KO) of the locus in HL60 promyeloblast cells. KO cells also displayed dramatically dysregulated endolysosomal pH regulation. Together, our data show that the rs35907548 risk allele affects multiple aspects of cellular physiology and may directly contribute to SLE.

A Non-Coding Variant in SLC15A4 Modulates Enhancer Activity and Lysosomal Deacidification Linked to Lupus Susceptibility

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a strong genetic basis. Despite the identification of several single nucleotide polymorphisms (SNPs) near the SLC15A4 gene that are significantly associated with SLE across multiple populations, specific causal SNP(s) and molecular mechanisms responsible for disease susceptibility are unknown. To address this gap, we employed bioinformatics, expression quantitative trait loci (eQTLs), and 3D chromatin interaction analysis to nominate a likely functional variant, rs35907548, in an active intronic enhancer of SLC15A4 . Through luciferase reporter assays followed by chromatin immunoprecipitation (ChIP)-qPCR, we observed significant allele-specific enhancer effects of rs35907548 in diverse cell lines. The rs35907548 risk allele T is associated with increased regulatory activity and target gene expression, as shown by eQTLs and chromosome conformation capture (3C)-qPCR. The latter revealed long-range chromatin interactions between the rs35907548 enhancer and the promoters of SLC15A4, GLTLD1 , and an uncharacterized lncRNA. The enhancer-promoter interactions and expression effects were validated by CRISPR/Cas9 knock-out (KO) of the locus in HL60 promyeloblast cells. KO cells also displayed dramatically dysregulated endolysosomal pH regulation. Together, our data show that the rs35907548 risk allele affects multiple aspects of cellular physiology and may directly contribute to SLE.

Higher Genetic Risk Loads Confer More Diverse Manifestations and Higher Risk of Lupus Nephritis in Systemic Lupus Erythematosus

OBJECTIVE

Systemic lupus erythematosus (SLE) is a highly heritable complex disorder with heterogeneous clinical manifestations. In this study, we aimed to identify the genetic risk load using clinical and serological manifestations in SLE patients.

METHODS

We genotyped a total of 1,655 Korean patients with SLE (n = 1,243 as a discovery set and n = 412 as a replication set) using a customized genome-wide single-nucleotide polymorphism (SNP) array, KoreanChip. A weighted genetic risk score (wGRS) for an individual was calculated from 112 well-validated non-HLA SNPs and HLA haplotypes of SLE-risk loci. We analyzed associations between individual wGRS and clinical SLE subphenotypes and autoantibodies using multivariable linear or logistic regression adjusted by onset age, sex, and disease duration.

RESULTS

Childhood-onset SLE (<16 years) conferred the highest genetic risk compared with adult-onset (16-50 years) or late-onset (>50 years) SLE (P = 6.8 × 10-6 ). High wGRS significantly increased associations with SLE manifestations, regardless of onset age, sex, and disease duration. Individual wGRS significantly correlated positively with more clinical American College of Rheumatology criteria (β = 0.143, P = 1.8 × 10-6 ). Subphenotype analysis revealed significant associations between the highest and lowest wGRS quartile with risk of renal disorder (hazard ratio [HR] 1.74, P = 2.2 × 10-8 ) and anti-Sm antibody production (HR 1.85, P = 2.8 × 10-5 ). Higher wGRS markedly modulated the pathogenesis of proliferative and membranous lupus nephritis class III or IV (HR 1.98, P = 1.6 × 10-5 ) and class V (HR 2.79, P = 1.0 × 10-3 ), but especially lupus nephritis class V in anti-Sm-positive SLE (area under the curve 0.68, P = 1.8 × 10-4 ).

CONCLUSION

Patients with SLE and high wGRS tended to have earlier age of SLE onset, higher anti-Sm antibody positivity, and more diverse clinical phenotypes. Genetic profiling may predict high risk for lupus nephritis and a diverse clinical course in SLE patients.

Phenotype Risk Score but Not Genetic Risk Score Aids in Identifying Individuals With Systemic Lupus Erythematosus in the Electronic Health Record

OBJECTIVE

Systemic lupus erythematosus (SLE) poses diagnostic challenges. We undertook this study to evaluate the utility of a phenotype risk score (PheRS) and a genetic risk score (GRS) to identify SLE individuals in a real-world setting.

METHODS

Using a de-identified electronic health record (EHR) database with an associated DNA biobank, we identified 789 SLE cases and 2,261 controls with available MEGAEX genotyping. A PheRS for SLE was developed using billing codes that captured American College of Rheumatology SLE criteria. We developed a GRS with 58 SLE risk single-nucleotide polymorphisms (SNPs).

RESULTS

SLE cases had a significantly higher PheRS (mean ± SD 7.7 ± 8.0 versus 0.8 ± 2.0 in controls; P < 0.001) and GRS (mean ± SD 12.2 ± 2.3 versus 11.0 ± 2.0 in controls; P < 0.001). Black individuals with SLE had a higher PheRS compared to White individuals (mean ± SD 10.0 ± 10.1 versus 7.1 ± 7.2, respectively; P = 0.002) but a lower GRS (mean ± SD 9.0 ± 1.4 versus 12.3 ± 1.7, respectively; P < 0.001). Models predicting SLE that used only the PheRS had an area under the curve (AUC) of 0.87. Adding the GRS to the PheRS resulted in a minimal difference with an AUC of 0.89. On chart review, controls with the highest PheRS and GRS had undiagnosed SLE.

CONCLUSION

We developed a SLE PheRS to identify established and undiagnosed SLE individuals. A SLE GRS using known risk SNPs did not add value beyond the PheRS and was of limited utility in Black individuals with SLE. More work is needed to understand the genetic risks of SLE in diverse populations.

Childhood-onset systemic lupus erythematosus: characteristics and the prospect of glucocorticoid pulse therapy

Childhood-onset systemic lupus erythematosus (cSLE) is an autoimmune disease that results in significant damage and often needs more aggressive treatment. Compared to adult-onset SLE, cSLE has a stronger genetic background and more prevalent elevated type I Interferon expression. The management of cSLE is more challenging because the disease itself and treatment can affect physical, psychological and emotional growth and development. High dose oral glucocorticoid (GC) has become the rule for treating moderate to severe cSLE activity. However, GC-related side effects and potential toxicities are problems that cannot be ignored. Recent studies have suggested that GC pulse therapy can achieve disease remission rapidly and reduce GC-related side effects with a reduction in oral prednisone doses. This article reviews characteristics, including pathogenesis and manifestations of cSLE, and summarized the existing evidence on GC therapy, especially on GC pulse therapy in cSLE, followed by our proposal for GC therapy according to the clinical effects and pathogenesis.

The Role of Genetic Risk Factors in Pathogenesis of Childhood-Onset Systemic Lupus Erythematosus

The pathogenesis of childhood-onset systemic lupus erythematosus (cSLE) is complex and not fully understood. It involves three key factors: genetic risk factors, epigenetic mechanisms, and environmental triggers. Genetic factors play a significant role in the development of the disease, particularly in younger individuals. While cSLE has traditionally been considered a polygenic disease, it is now recognized that in rare cases, a single gene mutation can lead to the disease. Although these cases are uncommon, they provide valuable insights into the disease mechanism, enhance our understanding of pathogenesis and immune tolerance, and facilitate the development of targeted treatment strategies. This review aims to provide a comprehensive overview of both monogenic and polygenic SLE, emphasizing the implications of specific genes in disease pathogenesis. By conducting a thorough analysis of the genetic factors involved in SLE, we can improve our understanding of the underlying mechanisms of the disease. Furthermore, this knowledge may contribute to the identification of effective biomarkers and the selection of appropriate therapies for individuals with SLE.

Systemic Lupus Erythematosus Patients with DNASE1L3·Deficiency Have a Distinctive and Specific Genic Circular DNA Profile in Plasma

Cell-free (cf) extrachromosomal circular DNA (eccDNA) has a potential clinical application as a biomarker. Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with a complex immunological pathogenesis, associated with autoantibody synthesis. A previous study found that SLE patients with deoxyribonuclease 1-like 3 (DNASE1L3) deficiency exhibit changes in the frequency of short and long eccDNA in plasma compared to controls. Here, using the DifCir method for differential analysis of short-read sequenced purified eccDNA data based on the split-read signal of the eccDNA on circulomics data, we show that SLE patients with DNASE1L3 deficiency have a distinctive profile of eccDNA excised by gene regions compared to controls. Moreover, this profile is specific; cf-eccDNA from the top 93 genes is detected in all SLE with DNASE1L3 deficiency samples, and none in the control plasma. The top protein coding gene producing eccDNA-carrying gene fragments is the transcription factor BARX2, which is involved in skeletal muscle morphogenesis and connective tissue development. The top gene ontology terms are ‘positive regulation of torc1 signaling’ and ‘chondrocyte development’. The top Harmonizome terms are ‘lymphopenia’, ‘metabolic syndrome x’, ‘asthma’, ‘cardiovascular system disease‘, ‘leukemia’, and ‘immune system disease’. Here, we show that gene associations of cf-eccDNA can serve as a biomarker in the autoimmune rheumatic diseases.

Trans-ancestry, Bayesian meta-analysis discovers 20 novel risk loci for inflammatory bowel disease in an African American, East Asian and European cohort

Inflammatory bowel disease (IBD) is an immune-mediated chronic intestinal disorder with major phenotypes: ulcerative colitis (UC) and Crohn's disease (CD). Multiple studies have identified over 240 IBD susceptibility loci. However, most studies have centered on European (EUR) and East Asian (EAS) populations. The prevalence of IBD in non-EUR, including African Americans (AAs), has risen in recent years. Here we present the first attempt to identify loci in AAs using a trans-ancestry Bayesian approach (MANTRA) accounting for heterogeneity between diverse ancestries while allowing for the similarity between closely related populations. We meta-analyzed genome-wide association studies (GWAS) and Immunochip data from a 2015 EUR meta-analysis of 38 155 IBD cases and 48 485 controls and EAS Immunochip study of 2824 IBD cases and 3719 controls, and our recent AA IBD GWAS of 2345 cases and 5002 controls. Across the major IBD phenotypes, we found significant evidence for 92% of 205 loci lead SNPs from the 2015 meta-analysis, but also for three IBD loci only established in latter studies. We detected 20 novel loci, all containing immunity-related genes or genes with other evidence for IBD or immune-mediated disease relevance: PLEKHG5;TNFSFR25 (encoding death receptor 3, receptor for TNFSF15 gene product TL1A), XKR6, ELMO1, BC021024;PI4KB;PSMD4 and APLP1 for IBD; AUTS2, XKR6, OSER1, TET2;AK094561, BCAP29 and APLP1 for CD; and GABBR1;MOG, DQ570892, SPDEF;ILRUN, SMARCE1;CCR7;KRT222;KRT24;KRT25, ANKS1A;TCP11, IL7, LRRC18;WDFY4, XKR6 and TNFSF4 for UC. Our study highlights the value of combining low-powered genomic studies from understudied populations of diverse ancestral backgrounds together with a high-powered study to enable novel locus discovery, including potentially important therapeutic IBD gene targets.

Genetic load in incomplete lupus erythematosus

OBJECTIVE

Patients with incomplete lupus erythematosus (ILE) have lupus features but insufficient criteria for SLE classification. Some patients with ILE transition to SLE, but most avoid major organ involvement. This study tested whether the milder disease course in ILE is influenced by reduced SLE risk allele genetic load.

METHODS

We calculated the genetic load based on 99 SLE-associated risk alleles in European American patients with SLE (≥4 American College of Rheumatology (ACR) 1997 criteria, n=170), patients with ILE (3 ACR 1997 criteria, n=169), a subset of patients with ILE not meeting Systemic Lupus International Collaborating Clinics (SLICC) classification (ILESLICC, n=119) and healthy controls (n=133). Unweighted genetic loads were calculated as the total sum of risk alleles for each individual, while weighted genetic loads were defined as the sum of risk alleles multiplied by the natural logarithm of the previously published OR of each risk allele for SLE susceptibility.

RESULTS

The median unweighted and weighted SLE risk allele genetic load was significantly greater in patients with ILE (unweighted: 81, p value=0.01; weighted: 16.3, p value=0.001) and patients with SLE (80, p value=0.02; 16.29, p value=0.0006) compared with healthy controls (78, 15.76). Patients with ILESLICC trended towards an increased genetic load, although not statistically significant (unweighted: 80, p value=0.14; weighted: 16.05, p value=0.07). However, the median genetic load did not significantly differ between ILE and SLE, and genetic load did not differentiate patients with ILE and SLE (area under the curve=0.51, p=0.78) by receiver operator characteristic analysis.

CONCLUSIONS

Patients with ILE and SLE have comparable genetic loads of SLE risk loci, suggesting similar genetic predispositions between these conditions. Phenotypical differences between SLE and ILE may instead be influenced by ILE-specific variants and gene-environment interactions.

Genome-wide association study identifies Sjögren's risk loci with functional implications in immune and glandular cells

Sjögren's disease is a complex autoimmune disease with twelve established susceptibility loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant (GWS) regions in Sjögren's cases of European ancestry: CD247, NAB1, PTTG1-MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2, SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08. Interrogation of bioinformatics databases refine the associations, define local regulatory networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to >40. Many GWS SNPs are eQTLs for genes within topologically associated domains in immune cells and/or eQTLs in the main target tissue, salivary glands.

Recent advances in understanding the genetic basis of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a polygenic chronic autoimmune disease leading to multiple organ damage. A large heritability of up to 66% is estimated in SLE, with roughly 180 reported susceptibility loci that have been identified mostly by genome-wide association studies (GWASs) and account for approximately 30% of genetic heritability. A vast majority of risk variants reside in non-coding regions, which makes it quite challenging to interpret their functional implications in the SLE-affected immune system, suggesting the importance of understanding cell type-specific epigenetic regulation around SLE GWAS variants. The latest genetic studies have been highly fruitful as several dozens of SLE loci were newly discovered in the last few years and many loci have come to be understood in systemic approaches integrating GWAS signals with other biological resources. In this review, we summarize SLE-associated genetic variants in both the major histocompatibility complex (MHC) and non-MHC loci, examining polygenetic risk scores for SLE and their associations with clinical features. Finally, variant-driven pathogenetic functions underlying genetic associations are described, coupled with discussion about challenges and future directions in genetic studies on SLE.

Genome-wide assessment of genetic risk for systemic lupus erythematosus and disease severity

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 (P_cohort1 = 2.44e−08; P_cohort2 = 0.00205) and a significant negative correlation with age of SLE onset (P_cohort1 = 1.76e−12; P_cohort2 = 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.

Systemic Lupus Erythematosus in Children and Young People

PURPOSE OF REVIEW

Juvenile-onset systemic lupus erythematosus ((j)SLE) is an autoimmune/inflammatory disease that results in significant damage and disability. When compared to patients with disease onset in adulthood, jSLE patients exhibit increased disease activity, damage and require more aggressive treatments. This manuscript summarises age-specific pathogenic mechanisms and underscores the need for age group-specific research, classification and treatment.

RECENT FINDINGS

Genetic factors play a significant role in the pathophysiology of jSLE, as > 7% of patients develop disease as a result of single gene mutations. Remaining patients carry genetic variants that are necessary for disease development, but require additional factors. Increased 'genetic impact' likely contributes to earlier disease onset and more severe phenotypes. Epigenetic events have only recently started to be addressed in jSLE, and add to the list of pathogenic mechanisms that may serve as biomarkers and/or treatment targets. To allow meaningful and patient-oriented paediatric research, age-specific classification criteria and treatment targets require to be defined as currently available tools established for adult-onset SLE have limitations in the paediatric cohort. Significant progress has been made in understanding the pathophysiology of jSLE. Meaningful laboratory and clinical research can only be performed using age group-specific tools, classification criteria and treatment targets.

Relationship Between Genetic Risk and Age of Diagnosis in Systemic Lupus Erythematosus

OBJECTIVE

Specific risk alleles for childhood-onset systemic lupus erythematosus SLE (cSLE) vs adult-onset SLE (aSLE) patients have not been identified. The aims of this study were to determine if there is an association (1) between non-HLA-related genetic risk score (GRS) and age of SLE diagnosis, and (2) between HLA-related GRS and age of SLE diagnosis.

METHODS

Genomic DNA was obtained from 2001 multiethnic patients and genotyped using the Immunochip. Following quality control, genetic risk counting (GRCS), weighted (GRWS), standardized counting (GRSCS), and standardized weighted (GRSWS) scores were calculated based on independent single-nucleotide polymorphisms from validated SLE loci. Scores were analyzed in a regression model and adjusted by sex and ancestral population.

RESULTS

The analyzed cohort consisted of 1540 patients: 1351 females and 189 males (675 cSLE and 865 aSLE). There were significant negative associations between all non-HLA GRS and age of SLE diagnosis: P = 0.011 and r² = 0.175 for GRWS; P = 0.008 and r² = 0.178 for GRSCS; P = 0.002 and r² = 0.176 for GRSWS (higher GRS correlated with lower age of diagnosis.) All HLA GRS showed significant positive associations with age of diagnosis: P = 0.049 and r² = 0.176 for GRCS; P = 0.022 and r² = 0.176 for GRWS; P = 0.022 and r² = 0.176 for GRSCS; P = 0.011 and r² = 0.177 for GRSWS (higher GRS correlated with higher age of diagnosis).

CONCLUSION

Our data suggest that there is a linear relationship between genetic risk and age of SLE diagnosis and that HLA and non-HLA GRS are associated with age of diagnosis in opposite directions.

A genome-wide multiphenotypic association analysis identified common candidate genes for subjective well-being, depressive symptoms and neuroticism

Subjective well-being (SWB), depressive symptoms, and neuroticism are common and vital traits of mental disorders. Genetic mechanisms of SWB, depressive symptoms and neuroticism remain elusive now. The large-scale GWAS summary datasets of SWB (n = 229,883), depressive symptoms (n = 180,866), and neuroticism (n = 170,911) were obtained from published studies. MASH tool was applied to the GWAS datasets for identifying candidate SNPs shared by SWB, depressive symptoms and neuroticism. SNPs detected by MASH, were then mapped to target genes considering regulatory SNP (rSNP), methylated quantitative trait locus (MeQTL) and the SNPs near to known genes. Gene set enrichment analysis (GSEA) was conducted by the FUMA platform. A total of 122 candidate SNPs were detected by MASH analysis, mapping to 29 target genes, such as CLDN23, MSRA and XKR6. GO enrichment analysis identified multiple immune related gene sets for SWB, depressive symptoms and neuroticism, such as GSE2770_UNTREATED_VS_IL4_TREATED_ACT_CD4_TCELL_48H_DN (P = 7.32 × 10^-3), GSE6259_FLT3L_INDUCED_DEC205_POS_DC_VS_CD4_TCELL_DN (P = 2.52 × 10^-2). We also found some mental disorders related gene sets were associated with three phenotypes, such as mood instability (P = 1.15 × 10^-6) and neuroticism (P = 1.72 × 10^-6). We identified multiple candidate genes and GO terms shared by SWB, depressive symptoms and neuroticism. Our results support the overlapping genetic mechanisms, and suggest a functional correlation between immunity and SWB, depressive symptoms and neuroticism.

Association of systemic lupus erythematosus (SLE) genetic susceptibility loci with lupus nephritis in childhood-onset and adult-onset SLE

OBJECTIVE

LN is one of the most common and severe manifestations of SLE. Our aim was to test the association of SLE risk loci with LN risk in childhood-onset SLE (cSLE) and adult-onset SLE (aSLE).

METHODS

Two Toronto-based tertiary care SLE cohorts included cSLE (diagnosed <18 years) and aSLE patients (diagnosed ⩾18 years). Patients met ACR and/or SLICC SLE criteria and were genotyped on the Illumina Multi-Ethnic Global Array or Omni1-Quad arrays. We identified those with and without biopsy-confirmed LN. HLA and non-HLA additive SLE risk-weighted genetic risk scores (GRSs) were tested for association with LN risk in logistic models, stratified by cSLE/aSLE and ancestry. Stratified effect estimates were meta-analysed.

RESULTS

Of 1237 participants, 572 had cSLE (41% with LN) and 665 had aSLE (30% with LN). Increasing non-HLA GRS was significantly associated with increased LN risk [odds ratio (OR) = 1.26; 95% CI 1.09, 1.46; P = 0.0006], as was increasing HLA GRS in Europeans (OR = 1.55; 95% CI 1.07, 2.25; P = 0.03). There was a trend for stronger associations between both GRSs and LN risk in Europeans with cSLE compared with aSLE. When restricting cases to proliferative LN, the magnitude of these associations increased for both the non-HLA (OR = 1.30; 95% CI 1.10, 1.52; P = 0.002) and HLA GRS (OR = 1.99; 95% CI 1.29, 3.08; P = 0.002).

CONCLUSION

We observed an association between known SLE risk loci and LN risk in children and adults with SLE, with the strongest effect observed among Europeans with cSLE. Future studies will include SLE-risk single nucleotide polymorphisms specific to non-European ancestral groups and validate findings in an independent cohort.

XKR6 rs7014968 SNP Increases Serum Total Cholesterol Levels and the Risk of Coronary Heart Disease and Ischemic Stroke

The X Kell blood group complex subunit-related family member 6 (XKR6) gene single-nucleotide polymorphisms (SNPs) have been associated with serum lipid profiles and the risk of coronary heart disease (CHD) and ischemic stroke (IS) in several previous studies, but the association between the XKR6 rs7014968 SNP and serum lipid levels and the risk of CHD and IS has not been detected previously. This study aims to explore the association between the XKR6 rs7014968 SNP and serum lipid traits and the susceptibility to CHD and IS in the Guangxi Han Chinese population. Snapshot technology was used to determine the genotypes of the XKR6 rs7014968 SNP in 624 controls, 588 patients with CHD, and 544 patients with IS. The XKR6 rs7014968C allele carriers in the control group had higher serum total cholesterol (TC) levels than the C allele noncarriers (P = .025). The XKR6 rs7014968C allele carriers also had an increased risk of CHD and IS (P < .05-.01). Stratified analysis showed that the patients with the rs7014968C allele in the female, age >60 years, body mass index (BMI) >24 kg/m², and hypertension subgroups had a higher risk of CHD than those in the subgroup counterparts. The patients with the rs7014968C allele in the male, BMI > 24 kg/m², smoker, and hypertension subgroups also had a higher risk of IS than those in the subgroup counterparts. These results suggest that the XKR6 rs7014968 SNP is likely to increase the risk of CHD and IS by increasing serum TC levels in our study populations.

Identifying damage clusters in patients with systemic lupus erythematosus

AIM

Systemic lupus erythematosus (SLE) causes irreversible damage to organ systems. Recently, evidence has been obtained for subphenotypes of SLE. This study aimed to identify damage clusters and compare the associated clinical manifestations, SLE disease activity, mortality, and genetic risk scores (GRS).

METHODS

The study was conducted on the Hanyang BAE lupus cohort. Patients with disease duration <5 years were excluded to minimize confounding effects of disease duration. They were grouped into 3 clusters based on the Systemic Lupus International Collaborating Clinics Damage Index using k-means cluster analysis.

RESULTS

Among the 1130 analyzed patients, musculoskeletal damage was most prevalent (20.2%), followed by ocular (11.4%), renal (10.5%), and neuropsychiatric damage (10.2%). Three significantly different damage clusters were identified. Patients in cluster 1 (n = 824) showed the least damage. Cluster 2 (n = 195) was characterized by frequent renal (55.4%) and ocular (58.0%) damage, and cluster 3 (n = 111) was dominated by neuropsychiatric (100%) and musculoskeletal damage (35.1%). Cluster 2 had the highest adjusted mean AMS (adjusted mean SLE Disease Activity Index score; mean ± SD: 5.4 ± 2.9), while cluster 3 had the highest mortality (14.4%). Weighted GRS did not differ significantly between the clusters.

CONCLUSION

Patients in prevalent renal and ocular damage cluster had the highest AMS scores, while the cluster with frequent neuropsychiatric damage had the highest mortality.

Update on the Genetics of Systemic Lupus Erythematosus: Genome-Wide Association Studies and Beyond

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease of complex etiology that primarily affects women of childbearing age. The development of SLE is attributed to the breach of immunological tolerance and the interaction between SLE-susceptibility genes and various environmental factors, resulting in the production of pathogenic autoantibodies. Working in concert with the innate and adaptive arms of the immune system, lupus-related autoantibodies mediate immune-complex deposition in various tissues and organs, leading to acute and chronic inflammation and consequent end-organ damage. Over the past two decades or so, the impact of genetic susceptibility on the development of SLE has been well demonstrated in a number of large-scale genetic association studies which have uncovered a large fraction of genetic heritability of SLE by recognizing about a hundred SLE-susceptibility loci. Integration of genetic variant data with various omics data such as transcriptomic and epigenomic data potentially provides a unique opportunity to further understand the roles of SLE risk variants in regulating the molecular phenotypes by various disease-relevant cell types and in shaping the immune systems with high inter-individual variances in disease susceptibility. In this review, the catalogue of SLE susceptibility loci will be updated, and biological signatures implicated by the SLE-risk variants will be critically discussed. It is optimistically hoped that identification of SLE risk variants will enable the prognostic and therapeutic biomarker armamentarium of SLE to be strengthened, a major leap towards precision medicine in the management of the condition.

Immunomics in Pediatric Rheumatic Diseases

The inherent complexity in the immune landscape of pediatric rheumatic disease necessitates a holistic system approach. Uncertainty in the mechanistic workings and etiological driving forces presents difficulty in personalized treatments. The development and progression of immunomics are well suited to deal with this complexity. Immunomics encompasses a spectrum of biological processes that entail genomics, transcriptomics, epigenomics, proteomics, and cytomics. In this review, we will discuss how various high dimensional technologies in immunomics have helped to grow a wealth of data that provide salient clues and biological insights into the pathogenesis of autoimmunity. Interfaced with critical unresolved clinical questions and unmet medical needs, these platforms have helped to identify candidate immune targets, refine patient stratification, and understand treatment response or resistance. Yet the unprecedented growth in data has presented both opportunities and challenges. Researchers are now facing huge heterogeneous data sets from different origins that need to be integrated and exploited for further data mining. We believe that the utilization and integration of these platforms will help unravel the complexities and expedite both discovery and validation of clinical targets.