GWAS identifies novel SLE susceptibility genes and explains the association of the HLA region

Systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a multisystemic autoimmune disease characterised by the presence of autoantibodies towards nuclear antigens, immune complex deposition, and chronic inflammation at classic target organs such as skin, joints, and kidneys. Despite substantial advances in the diagnosis and management of SLE, the burden of disease remains high. It is important to appreciate the typical presentations and the diagnostic process to facilitate early referral and diagnosis for patients. In most patients, constitutional, mucocutaneous, and musculoskeletal symptoms represent the earliest complaints; these symptoms can include fatigue, lupus-specific rash, mouth ulcers, alopecia, joint pain, and myalgia. In this Seminar we will discuss a diagnostic approach to symptoms in light of the latest classification criteria, which include a systematic evaluation of clinical manifestations (weighted within each domain) and autoantibody profiles (such as anti-double-stranded DNA, anti-Sm, hypocomplementaemia, or antiphospholipid antibodies). Non-pharmacotherapy management is tailored to the individual, with specific lifestyle interventions and patient education to improve quality of life and medication (such as hydroxychloroquine or immunosuppressant) adherence. In the last decade, there have been a few major breakthroughs in approved treatments for SLE and lupus nephritis, such as belimumab, anifrolumab, and voclosporin. However the disease course remains variable and mortality unacceptably high. Access to these expensive medications has also been restricted across different regions of the world. Nonetheless, understanding of treatment goals and strategies has improved. We recognise that the main goal of treatment is the achievement of remission or low disease activity. Comorbidities due to both disease activity and treatment adverse effects, especially infections, osteoporosis, and cardiovascular disease, necessitate vigilant prevention and management strategies. Tailoring treatment options to achieve remission, while balancing treatment-related comorbidities, are priority areas of SLE management.

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKϵ. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a new regulatory pathway involving rs2297550, Ikaros, and IKKϵ implicated by human genetics in risk for SLE.

Candidate Genetic and Molecular Drivers of Dysregulated Adaptive Immune Responses After Traumatic Brain Injury

Abstract Neuroinflammation is a significant and modifiable cause of secondary injury after traumatic brain injury (TBI), driven by both central and peripheral immune responses. A substantial proportion of outcome after TBI is genetically mediated, with an estimated heritability effect of around 26%, but because of the comparatively small datasets currently available, the individual drivers of this genetic effect have not been well delineated. A hypothesis-driven approach to analyzing genome-wide association study (GWAS) datasets reduces the burden of multiplicity testing and allows variants with a high prior biological probability of effect to be identified where sample size is insufficient to withstand data-driven approaches. Adaptive immune responses show substantial genetically mediated heterogeneity and are well established as a genetic source of risk for numerous disease states; importantly, HLA class II has been specifically identified as a locus of interest in the largest TBI GWAS study to date, highlighting the importance of genetic variance in adaptive immune responses after TBI. In this review article we identify and discuss adaptive immune system genes that are known to confer strong risk effects for human disease, with the dual intentions of drawing attention to this area of immunobiology, which, despite its importance to the field, remains under-investigated in TBI and presenting high-yield testable hypotheses for application to TBI GWAS datasets.

B cell polygenic risk scores associate with anti-dsDNA antibodies and nephritis in systemic lupus erythematosus

OBJECTIVE

B cell function and autoantibodies are important in SLE pathogenesis. In this work, we aimed to investigate the impact of cumulative SLE B cell genetics on SLE subphenotype and autoantibody profile.

METHODS

Female patients with SLE (n=1248) and healthy controls (n=400) were genotyped using Illumina's Global Screening Array. Two polygenic risk scores (PRSs), one representing B cell genes and the other B cell activation genes, were calculated for each individual using risk loci for SLE in genes assigned to B cell-related pathways according to the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology and Reactome Databases.

RESULTS

Double-stranded DNA (dsDNA) antibodies were more prevalent among patients with a high compared with a low SLE B cell PRS (OR 1.47 (1.07 to 2.01), p=0.018), and effect sizes were augmented in patients with human leucocyte antigen (HLA) risk haplotypes HLA-DRB1*03:01 and HLA-DRB1*15:01 (DRB1*03/15 -/- (OR 0.99 (0.56 to 1.77), p=0.98; DRB1*03/15 +/- or -/+ (OR 1.64 (1.06 to 2.54), p=0.028; and DRB1*03/15 +/+ (OR 4.47 (1.21 to 16.47), p=0.024). Further, a high compared with a low B cell PRS was associated with low complement levels in DRB1*03/15 +/+ patients (OR 3.92 (1.22 to 12.64), p=0.022). The prevalence of lupus nephritis (LN) was higher in patients with a B cell activation PRS above the third quartile compared with patients below (OR 1.32 (1.00 to 1.74), p=0.048).

CONCLUSIONS

High genetic burden related to B cell function is associated with dsDNA antibody development and LN. Assessing B cell PRSs may be important in order to determine immunological pathways influencing SLE and to predict clinical phenotype.

Genetics of SLE: mechanistic insights from monogenic disease and disease-associated variants

The past few years have provided important insights into the genetic architecture of systemic autoimmunity through aggregation of findings from genome-wide association studies (GWAS) and whole-exome or whole-genome sequencing studies. In the prototypic systemic autoimmune disease systemic lupus erythematosus (SLE), monogenic disease accounts for a small fraction of cases but has been instrumental in the elucidation of disease mechanisms. Defects in the clearance or digestion of extracellular or intracellular DNA or RNA lead to increased sensing of nucleic acids, which can break B cell tolerance and induce the production of type I interferons leading to tissue damage. Current data suggest that multiple GWAS SLE risk alleles act in concert with rare functional variants to promote SLE development. Moreover, introduction of orthologous variant alleles into mice has revealed that pathogenic X-linked dominant and recessive SLE can be caused by novel variants in TLR7 and SAT1, respectively. Such bespoke models of disease help to unravel pathogenic pathways and can be used to test targeted therapies. Cell type-specific expression data revealed that most GWAS SLE risk genes are highly expressed in age-associated B cells (ABCs), which supports the view that ABCs produce lupus autoantibodies and contribute to end-organ damage by persisting in inflamed tissues, including the kidneys. ABCs have thus emerged as key targets of promising precision therapeutics.

Translational implications of newly characterized pathogenic pathways in systemic lupus erythematosus

Improved characterization of relevant pathogenic pathways in systemic lupus erythematosus (SLE) has been further delineated over the last decades. This led to the development of targeted treatments including belimumab and anifrolumab, which recently became available in clinics. Therapeutic targets in SLE encompass interferon (IFN) signaling, B-T costimulation including immune checkpoints, and increasing modalities of B lineage targeting, such as chimeric antigen receptor (CAR) T cells directed against CD19 or sequential anti-B cell targeting. Patient profiling based on characterization of underlying molecular abnormalities, often performed through comprehensive omics analyses, has recently been shown to better predict patients' treatment responses and also holds promise to unravel key molecular mechanisms driving SLE. SLE carries two key signatures, namely the IFN and B lineage/plasma cell signatures. Recent advances in SLE treatments clearly indicate that targeting innate and adaptive immunity is successful in such a complex autoimmune disease. Although those signatures may interact at the molecular level and provide the basis for the first selective treatments in SLE, it remains to be clarified whether these distinct treatments show different treatment responses among certain patient subsets. In fact, notwithstanding the remarkable amount of novel clues for innovative SLE treatment, harmonization of big data within tailored treatment strategies will be instrumental to better understand and treat this challenging autoimmune disorder. This review will provide an overview of recent improvements in SLE pathogenesis, related insights by analyses of big data and machine learning as well as technical improvements in conducting clinical trials with the ultimate goal that translational research results in improved patient outcomes.

Pathogenesis of systemic lupus erythematosus: risks, mechanisms and therapeutic targets

Research elucidating the pathogenesis of systemic lupus erythematosus (SLE) has defined two critical families of mediators, type I interferon (IFN-I) and autoantibodies targeting nucleic acids and nucleic acid-binding proteins, as fundamental contributors to the disease. On the fertile background of significant genetic risk, a triggering stimulus, perhaps microbial, induces IFN-I, autoantibody production or most likely both. When innate and adaptive immune system cells are engaged and collaborate in the autoimmune response, clinical SLE can develop. This review describes recent data from genetic analyses of patients with SLE, along with current studies of innate and adaptive immune function that contribute to sustained IFN-I pathway activation, immune activation and autoantibody production, generation of inflammatory mediators and tissue damage. The goal of these studies is to understand disease mechanisms, identify therapeutic targets and stimulate development of therapeutics that can achieve improved outcomes for patients.

Transcriptome sequencing reveals novel molecular features of SLE severity

Introduction: Systemic lupus erythematosus (SLE) is an autoimmune disorder characterized by the production of autoantibodies, immune complex deposition, and tissue/organ damage. In this study, we aimed to identify molecular features and signaling pathways associated with SLE severity using RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), and clinical parameters. Methods: We analyzed transcriptome profiles of 45 SLE patients, grouped into mild (mSLE, SLEDAI ≤ 9) and severe (sSLE, SLEDAI > 9) based on SLE Disease Activity Index (SLEDAI) scores. We also collected clinical data on anti-dsDNA, ANA, ESR, CRP, snRNP, AHA, and anti-Smith antibody status for each patient. Results: By comparing gene expression across groups, we identified 12 differentially expressed genes (DEGs), including 7 upregulated (CEACAM6, UCHL1, ARFGEF3, AMPH, SERPINB10, TACSTD2, and OTX1) and 5 downregulated (SORBS2, TRIM64B, SORCS3, DRAXIN, and PCDHGA10) DEGs in sSLE compared to mSLE. Furthermore, using the CIBERSORT algorithm, we found that Treg cells were significantly decreased in sSLE and negatively correlated with AMPH expression, which was mainly expressed in Treg cells from SLE patients according to public scRNA-seq data (GSE135779). Discussion: Overall, our findings shed light on the molecular mechanisms underlying SLE severity and provide insight into potential therapeutic targets.

Risk prediction models for incident systemic lupus erythematosus among women in the Nurses' health study cohorts using genetics, family history, and lifestyle and environmental factors

OBJECTIVE

Systemic lupus erythematosus (SLE) is a severe multisystem autoimmune disease that predominantly affects women. Its etiology is complex and multifactorial, with several known genetic and environmental risk factors, but accurate risk prediction models are still lacking. We developed SLE risk prediction models, incorporating known genetic, lifestyle and environmental risk factors, and family history.

METHODS

We performed a nested case-control study within the Nurses' Health Study cohorts (NHS). NHS began in 1976 and enrolled 121,700 registered female nurses ages 30-55 from 11 U.S. states; NHSII began in 1989 and enrolled 116,430 registered female nurses ages 25-42 from 14 U.S. states. Participants were asked about lifestyle, reproductive and environmental exposures, as well as medical information, on biennial questionnaires. Incident SLE cases were self-reported and validated by medical record review (Updated 1997 American College of Rheumatology classification criteria). Those with banked blood samples for genotyping (∼25% of each cohort), were selected and matched by age (± 4 years) and race/ethnicity to women who had donated a blood sample but did not develop SLE. Lifestyle and reproductive variables, including smoking, alcohol use, body mass index, sleep, socioeconomic status, U.S. region, menarche age, oral contraceptive use, menopausal status/postmenopausal hormone use, and family history of SLE or rheumatoid arthritis (RA) were assessed through the questionnaire prior to SLE diagnosis questionnaire cycle (or matched index date). Genome-wide genotyping results were used to calculate a SLE weighted genetic risk score (wGRS) using 86 published single nucleotide polymorphisms (SNPs) and 10 classical HLA alleles associated with SLE. We compared four sequential multivariable logistic regression models of SLE risk prediction, each calculating the area under the receiver operating characteristic curve (AUC): 1) SLE wGRS, 2) SLE/RA family history, 3) lifestyle, environmental and reproductive factors and 4) combining model 1-3 factors. Models were internally validated using a bootstrapped estimate of optimism of the AUC. We also examined similar sequential models to predict anti-dsDNA positive SLE risk.

RESULTS

We identified and matched 138 women who developed incident SLE to 1136 women who did not. Models 1-4 yielded AUCs 0.63 (95%CI 0.58-0.68), 0.64 (95%CI 0.59-0.68), 0.71(95% CI 0.66-0.75), and 0.76 (95% CI 0.72-0.81). Model 4 based on genetics, family history and eight lifestyle and environmental factors had best discrimination, with an optimism-corrected AUC 0.75. AUCs for similar models predicting anti-dsDNA positive SLE risk, were 0.60, 0.63, 0.81 and 0.82, with optimism corrected AUC of 0.79 for model 4.

CONCLUSION

A final model including SLE weighted genetic risk score, family history and eight lifestyle and environmental SLE risk factors accurately classified future SLE risk with optimism corrected AUC of 0.75. To our knowledge, this is the first SLE prediction model based on known risk factors. It might be feasibly employed in at-risk populations as genetic data are increasingly available and the risk factors easily assessed. The NHS cohorts include few non-White women and mean age at incident SLE was early 50s, calling for further research in younger and more diverse cohorts.

Genetic architecture of fresh-market tomato yield

BACKGROUND

The fresh-market tomato (Solanum lycopersicum) is bred for direct consumption and is selected for a high yield of large fruits. To understand the genetic variations (distinct types of DNA sequence polymorphism) that influence the yield, we collected the phenotypic variations in the yields of total fruit, extra-large-sized fruit, small-sized fruit, or red-colored fruit from 68 core inbred contemporary U.S. fresh-market tomatoes for three consecutive years and the genomic information in 8,289,741 single nucleotide polymorphism (SNP) positions from the whole-genome resequencing of these tomatoes.

RESULTS

Genome-wide association (GWA) mapping using the SNP data with or without SNP filtering steps using the regularization methods, validated with quantitative trait loci (QTL) linkage mapping, identified 18 significant association signals for traits evaluated. Among them, 10 of which were not located within genomic regions previously identified as being associated with fruit size/shape. When mapping-driven association signals [558 SNPs associated with 28 yield (component) traits] were used to calculate genomic estimated breeding values (GEBVs) of evaluated traits, the prediction accuracies of the extra-large-sized fruit and small-sized fruit yields were higher than those of the total and red-colored fruit yields, as we tested the generated breeding values in inbred tomatoes and F2 populations. Improved accuracy in GEBV calculation of evaluated traits was achieved by using 364 SNPs identified using the regularization methods.

CONCLUSIONS

Together, these results provide an understanding of the genetic variations underlying the heritable phenotypic variability in yield in contemporary tomato breeding and the information necessary for improving such economically important and complex quantitative trait through breeding.

Immunogenic self-peptides - the great unknowns in autoimmunity: Identifying T-cell epitopes driving the autoimmune response in autoimmune diseases

HLA-associated autoimmune diseases likely arise from T-cell-mediated autoimmune responses against certain self-peptides from the broad HLA-presented immunopeptidomes. The limited knowledge of the autoimmune target peptides has so far compromised the basic understanding of autoimmune pathogenesis. This is due to the complexity of antigen processing and presentation as well as the polyspecificity of T-cell receptors (TCRs), which pose high methodological challenges on the discovery of immunogenic self-peptides. HLA-class I molecules present peptides to CD8⁺ T cells primarily derived from cytoplasmic proteins. Therefore, HLA-class I-restricted autoimmune responses should be directed against target cells expressing the corresponding parental protein. In HLA-class II-associated diseases, the origin of immunogenic peptides is not pre-specified, because peptides presented by HLA-class II molecules to CD4⁺ T cells may originate from both extracellular and cellular self-proteins. The different origins of HLA-class I and class II presented peptides determine the respective strategy for the discovery of immunogenic self-peptides in approaches based on the TCRs isolated from clonally expanded pathogenic T cells. Both involve identifying the respective restricting HLA allele as well as determining the recognition motif of the TCR under investigation by peptide library screening, which is required to search for homologous immunogenic self-peptides. In HLA-class I-associated autoimmune diseases, identification of the target cells allows for defining the restricting HLA allotype from the 6 different HLA-class I alleles of the individual HLA haplotype. It furthermore limits the search for immunogenic self-peptides to the transcriptome or immunopeptidome of the target cells, although neoepitopes generated by peptide splicing or translational errors may complicate identification. In HLA class II-associated autoimmune diseases, the lack of a defined target cell and differential antigen processing in different antigen-presenting cells complicate identification of the HLA restriction of autoreactive TCRs from CD4⁺ T cells. To avoid that all corresponding HLA-class II allotypes have to be included in the peptide discovery, autoantigens defined by autoantibodies can guide the search for immunogenic self-peptides presented by the respective HLA-class II risk allele. The objective of this article is to highlight important aspects to be considered in the discovery of immunogenic self-peptides in autoimmune diseases.

Mendelian randomization and pathway analysis demonstrate shared genetic associations between lupus and coronary artery disease

Coronary artery disease (CAD) is a leading cause of death in patients with systemic lupus erythematosus (SLE). Despite clinical evidence supporting an association between SLE and CAD, pleiotropy-adjusted genetic association studies are limited and focus on only a few common risk loci. Here, we identify a net positive causal estimate of SLE-associated non-HLA SNPs on CAD by traditional Mendelian randomization (MR) approaches. Pathway analysis using SNP-to-gene mapping followed by unsupervised clustering based on protein-protein interactions (PPIs) identifies biological networks composed of positive and negative causal sets of genes. In addition, we confirm the casual effects of specific SNP-to-gene modules on CAD using only SNP mapping to each PPI-defined functional gene set as instrumental variables. This PPI-based MR approach elucidates various molecular pathways with causal implications between SLE and CAD and identifies biological pathways likely causative of both pathologies, revealing known and novel therapeutic interventions for managing CAD in SLE.

Lupus, DNA Methylation, and Air Pollution: A Malicious Triad

The pathogenesis of systemic lupus erythematosus (SLE) remains elusive to this day; however, genetic, epigenetic, and environmental factors have been implicated to be involved in disease pathogenesis. Recently, it was demonstrated that in systemic lupus erythematosus (SLE) patients, interferon-regulated genes are hypomethylated in naïve CD4⁺ T cells, CD19⁺ B lymphocytes, and CD14⁺ monocytes. This suggests that interferon-regulated genes may have been epigenetically poised in SLE patients for rapid expression upon stimulation by different environmental factors. Additionally, environmental studies have identified DNA (hypo)methylation changes as a potential mechanism of environmentally induced health effects in utero, during childhood and in adults. Finally, epidemiologic studies have firmly established air pollution as a crucial SLE risk factor, as studies showed an association between fine particulate matter (PM_2.5) and traditional SLE biomarkers related to disease flare, hospital admissions, and an increased SLEDAI score. In this review, the relationship between aberrant epigenetic regulation, the environment, and the development of SLE will be discussed.

Genetic associations with lymphomas in Polish patients: A pooled-DNA genome-wide association analysis

Several single nucleotide polymorphisms (SNPs) associated with susceptibility to Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma (DLBCL) have been identified. The aim of this study was to identify susceptibility loci for HL and DLBCL in Polish patients. Altogether, DLBCL (n = 218 and HL patients (n = 224) and healthy individuals (n = 1181) were recruited. Lymphoma diagnosis was based on standard criteria. Genome-wide association study (GWAS) was performed using pooled-DNA samples on llumina Infinium Omni2.5 Exome-8 v1.3, and selected loci were replicated by TaqMan SNP genotyping of individuals. GWAS detected thirteen and seven SNPs associated with DLBCL and HL, respectively. In the replication study, six and seven SNPs reached significance after correction for multiple testing in the DLBCL and HL cohorts, respectively. One and four SNPs associated with DLBCL and HL, respectively, were localized within, and two SNPs-near the major histocompatibility complex (MHC) region. In conclusion, the majority of loci associated with HL and DLBCL aetiology in previous studies have potential roles in immune function. Our pooled-DNA GWAS enabled the identification of several susceptibility loci for DLBCL and HL in the Polish population; some of them were mapped within or adjacent to the MHC, and other associated SNPs were located outside the MHC.

Human leucocyte antigens profiling in Malay female patients with systemic lupus erythematosus: are we the same or different?

OBJECTIVE

SLE is a heterogeneous autoimmune disease, in terms of clinical presentation, incidence and severity across diverse ethnic populations. We investigated the human leucocyte antigens (HLA) profile (ie, HLA-A, HLA-B and HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1 and HLA-DPB1) in Malaysian Malay female patients with SLE and determined the generalisability of the published HLA risk factors across different ethnic populations globally including Malaysia.

METHODS

One hundred Malay female patients with SLE were recruited between January 2016 and October 2017 from a nephrology clinic. All patients were genotyped for HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1 and HLA-DPB1 alleles using PCR sequence-specific oligonucleotides method on Luminex platform. A total of 951 HLA genotyped population-based Malay control subjects was used for association testing by means of OR with 95% CIs.

RESULTS

Our findings convincingly validated common associations between HLA-A*11 (OR=1.65, p=3.36×10^-3, corrected P (Pc)=4.03×10^-2) and DQB1*05:01 (OR=1.56, p=2.02×10^-2, Pc=non-significant) and SLE susceptibility in the Malay population. In contrast, DQB1*03:01 (OR=0.51, p=4.06×10^-4, Pc=6.50×10^-3) were associated with decreased risk of SLE in Malay population. Additionally, we also detected novel associations of susceptibility HLA genes (ie, HLA-B*38:02, DPA1*02:02, DPB1*14:01) and protective HLA genes (ie, DPA1*01:03). When comparing the current data with data from previously published studies from Caucasian, African and Asian populations, DRB1*15 alleles, DQB1*03:01 and DQA1*01:02 were corroborated as universal susceptibility and protective genes.

CONCLUSIONS

This study reveals multiple HLA alleles associated with susceptibility and protection against risk of developing SLE in Malay female population with renal disorders. In addition, the published data from different ethnic populations together with our study further support the notion that the genetic effects from association with DRB1*15:01/02, DQB1*03:01 and DQA1*01:02 alleles are generalised to multiple ethnic populations of Caucasian, African and Asian descents.

Genetic and transcriptomic analyses support a switch to lytic phase in Epstein Barr virus infection as an important driver in developing Systemic Lupus Erythematosus

To investigate the molecular mechanisms through which Epstein-Barr virus (EBV) may contribute to Systemic Lupus Erythematosus (SLE) pathogenesis, we interrogated SLE genetic risk loci for signatures of EBV infection. We first compared the gene expression profile of SLE risk genes across 459 different cell/tissue types. EBV-infected B cells (LCLs) had the strongest representation of highly expressed SLE risk genes. By determining an SLE risk allele effect on gene expression (expression quantitative trait loci, eQTL) in LCLs and 16 other immune cell types, we identified 79 SLE risk locus:gene pairs putatively interacting with EBV infection. A total of 10 SLE risk genes from this list (CD40, LYST, JAZF1, IRF5, BLK, IKZF2, IL12RB2, FAM167A, PTPRC and SLC15A) were targeted by the EBV transcription factor, EBNA2, differentially expressed between LCLs and B cells, and the majority were also associated with EBV DNA copy number, and expression level of EBV encoded genes. Our final gene network model based on these genes is suggestive of a nexus involving SLE risk loci and EBV latency III and B cell proliferation signalling pathways. Collectively, our findings provide further evidence to support the interaction between SLE risk loci and EBV infection that is in part mediated by EBNA2. This interplay may increase the tendency towards EBV lytic switching dependent on the presence of SLE risk alleles. These results support further investigation into targeting EBV as a therapeutic strategy for SLE.

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.

Characterizing RNA Pseudouridylation by Convolutional Neural Networks

Pseudouridine (Ψ) is the most prevalent post-transcriptional RNA modification and is widespread in small cellular RNAs and mRNAs. However, the functions, mechanisms, and precise distribution of Ψs (especially in mRNAs) still remain largely unclear. The landscape of Ψs across the transcriptome has not yet been fully delineated. Here, we present a highly effective model based on a convolutional neural network (CNN), called PseudoUridyLation Site Estimator (PULSE), to analyze large-scale profiling data of Ψ sites and characterize the contextual sequence features of pseudouridylation. PULSE, consisting of two alternatively-stacked convolution and pooling layers followed by a fully-connected neural network, can automatically learn the hidden patterns of pseudouridylation from the local sequence information. Extensive validation tests demonstrated that PULSE can outperform other state-of-the-art prediction methods and achieve high prediction accuracy, thus enabling us to further characterize the transcriptome-wide landscape of Ψ sites. We further showed that the prediction results derived from PULSE can provide novel insights into understanding the functional roles of pseudouridylation, such as the regulations of RNA secondary structure, codon usage, translation, and RNA stability, and the connection to single nucleotide variants. The source code and final model for PULSE are available at https://github.com/mlcb-thu/PULSE.

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.

Comprehensive analysis of the major histocompatibility complex in systemic sclerosis identifies differential HLA associations by clinical and serological subtypes

OBJECTIVE

The greatest genetic effect reported for systemic sclerosis (SSc) lies in the major histocompatibility complex (MHC) locus. Leveraging the largest SSc genome-wide association study, we aimed to fine-map this region to identify novel human leucocyte antigen (HLA) genetic variants associated with SSc susceptibility and its main clinical and serological subtypes.

METHODS

9095 patients with SSc and 17 584 controls genome-wide genotyped were used to impute and test single-nucleotide polymorphisms (SNPs) across the MHC, classical HLA alleles and their composite amino acid residues. Additionally, patients were stratified according to their clinical and serological status, namely, limited cutaneous systemic sclerosis (lcSSc), diffuse cutaneous systemic sclerosis (dcSSc), anticentromere (ACA), antitopoisomerase (ATA) and anti-RNApolIII autoantibodies (ARA).

RESULTS

Sequential conditional analyses showed nine SNPs, nine classical alleles and seven amino acids that modelled the observed associations with SSc. This confirmed previously reported associations with HLA-DRB1*11:04 and HLA-DPB1*13:01, and revealed a novel association of HLA-B*08:01. Stratified analyses showed specific associations of HLA-DQA1*02:01 with lcSSc, and an exclusive association of HLA-DQA1*05:01 with dcSSc. Similarly, private associations were detected in HLA-DRB1*08:01 and confirmed the previously reported association of HLA-DRB1*07:01 with ACA-positive patients, as opposed to the HLA-DPA1*02:01 and HLA-DQB1*03:01 alleles associated with ATA presentation.

CONCLUSIONS

This study confirms the contribution of HLA class II and reveals a novel association of HLA class I with SSc, suggesting novel pathways of disease pathogenesis. Furthermore, we describe specific HLA associations with SSc clinical and serological subtypes that could serve as biomarkers of disease severity and progression.

Inhibition of NLRC5 regulates cytokine expression in CD4+ T helper lymphocytes and prolongs murine islet and skin allograft survival

The purpose of this study was to study the effect of inhibiting NLRC5 expression and function on CD4 + T cells, and islet and skin transplantation in mice. A murine skin graft model and islet cell transplantation model were established, and the expression of NLRC5 was compared in rejection and immune tolerance groups. Mice spleen-derived CD4 + T cells were cultured, purified, and enriched in vitro, and transfected with the shRNA lentiviral vector NLRC5-RNAi-GFP. Changes in cytokine secretion were detected to understand changes in immunological function. Murine islet and skin transplantation models were injected with CD4 + T cells transfected with the lentivirus, and the survival time of the grafts and the levels of IFN-γ and IL-10 were compared between groups. The expression of NLRC5 mRNA in islet and skin grafts was significantly increased. In vitro experiments showed that the expression of IL-4 and IL-10 was up-regulated in CD4 + T cells, and T cells differentiation turned to Th2 after inhibition of NLRC5. In vivo experiments showed that inhibition of NLRC5 prolonged islet and skin graft survival. Pathological examination showed that the rejection of transplanted skin and islets in the NLRC5-RNAi group was mild, and there was a correlation between high expression of NLRC5 and rejection of mouse islet and skin grafts. In summary, inhibition of NLRC5 can prolong islet and skin graft survival induce transplant immune tolerance through induction of the secretion of Th2 cytokines by CD4 + T cells.

SEC61G identified as a prognostic biomarker of head and neck squamous cell carcinoma

Purpose

It is of obvious interest to identify clinical prognosis-related oncogenes in HNSCC (head and neck squamous cell carcinoma).

Methods

Based on the available datasets within the TCGA (The Cancer Genome Atlas) and the GEO (Gene Expression Omnibus) databases, the potential mechanism of action of the SEC61G (SEC61 translocon subunit gamma) gene in HNSCC tumorigenesis was explored by several bioinformatics approaches.

Results

There was a higher expression level of SEC61G in primary HNSCC tumor tissues than in normal tissues. Moreover, highly expressed SEC61G was statistically associated with the poor survival prognosis of HNSCC patients. When HPV (human papilloma virus) was considered, we also observed a relatively lower proportion of “arm-level gain” and “high amplification” types of CNA (copy-number alteration) in the HNSCC-HPV (+) group than in the HNSCC-HPV (−) group. Additionally, we identified SEC61G CAN-correlated genes, such as CCT6A (chaperonin-containing TCP1 subunit 6A) and HUS1 (HUS1 checkpoint clamp component), and found a correlation between SEC61G copy-number segments and prognosis related to overall and progression-free survival intervals of HNSCC patients. Moreover, the molecular regulation mechanisms of the spliceosome, ribosome, proteasome degradation, cell adhesion, and immune infiltration of B and CD8⁺ T cells may contribute to the involvement of SEC61G in the pathogenesis of HNSCC.

Conclusions

The SEC61G gene was identified for the first time as a prognostic biomarker of HNSCC. The detailed underlying mechanism merits further research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00405-021-06955-7.

MS-Based HLA-II Peptidomics Combined With Multiomics Will Aid the Development of Future Immunotherapies

Immunotherapies have emerged to treat diseases by selectively modulating a patient's immune response. Although the roles of T and B cells in adaptive immunity have been well studied, it remains difficult to select targets for immunotherapeutic strategies. Because human leukocyte antigen class II (HLA-II) peptides activate CD4+ T cells and regulate B cell activation, proliferation, and differentiation, these peptide antigens represent a class of potential immunotherapy targets and biomarkers. To better understand the molecular basis of how HLA-II antigen presentation is involved in disease progression and treatment, systematic HLA-II peptidomics combined with multiomic analyses of diverse cell types in healthy and diseased states is required. For this reason, MS-based innovations that facilitate investigations into the interplay between disease pathologies and the presentation of HLA-II peptides to CD4+ T cells will aid in the development of patient-focused immunotherapies.

Risk of Systemic Lupus Erythematosus in Patients With Anti-phospholipid Syndrome: A Population-Based Study

Objective: To investigate the association between anti-phospholipid syndrome (APS) and the risk of newly diagnosed systemic lupus erythematosus (SLE). Methods: We used 2003-2013 data derived from Taiwan's National Health Insurance Research Database to conduct this nationwide, population-based. We identified AS patients newly diagnosed between 2005 to 2013 as the study group and applied age-sex matched (1:20) and propensity score-matched (PSM) (1:2) non-SLE individuals as controls. The association between APS and risk of incident SLE was determined by calculating hazard ratios (HRs) with 95% confidence intervals (CIs) using Cox proportional hazard regression analysis. Results: We identified 1,245 patients with APS as well as 24,900 age- and sex-matched non-APS controls and 727 APS patients as well as 1,454 PSM non-APS controls. We found that the risk for incident SLE in the APS group was 80.70 times higher than the non-APS group, and the association remained robust after PSM (HR, 28.55; 95% CI, 11.49-70.91). The increased risk for SLE in patients with APS mainly existed within 5 years after the diagnosis of APS. The sensitivity analyses found that the risk for SLE in patients with APS was consistent excluding patients with ITP/AIHA and using distinct definitions of SLE. Conclusion: The present population-based study revealed a robust association between SLE risk and recent APS and highlights the need for vigilance of SLE-associated symptoms in patients who had been diagnosed with APS.

Global discovery of lupus genetic risk variant allelic enhancer activity

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we construct a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 reveals 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

Thousands of genetic variants have been associated with lupus, but causal variants and mechanisms are unknown. Here, the authors combine a massively parallel reporter assay with genome-wide ChIP experiments to identify risk variants with allelic enhancer activity mediated through transcription factor binding.

STAT4 Is Largely Dispensable for Systemic Lupus Erythematosus-like Autoimmune- and Foreign Antigen-Driven Antibody-Forming Cell, Germinal Center, and Follicular Th Cell Responses

Genome-wide association studies identified variants in the transcription factor STAT4 gene and several other genes in the STAT4 signaling pathway, such as IL12A, IL12B, JAK2, and TYK2, which are associated with an increased risk of developing systemic lupus erythematosus (SLE) and other autoimmune diseases. Consistent with the genome-wide association studies data, STAT4 was shown to play an important role in autoimmune responses and autoimmunity development in SLE mouse models. Despite such important role for STAT4 in SLE development in mice and humans, little is known whether and how STAT4 may regulate extrafollicular Ab-forming cell (AFC) and follicular germinal center (GC) responses, two major pathways of autoreactive B cell development and autoantibody production. To our surprise, we found STAT4 to be largely dispensable for promoting autoimmune AFC and GC responses in various autoimmune- and SLE-prone mouse models, which strongly correlated with autoantibody production, and immune complex deposition and immune cell infiltration in the kidney. We further observed that STAT4 deficiency had no effects on AFC, GC, and Ag-specific Ab responses during protein Ag immunization or influenza virus infection. Additionally, CD4+ effector and follicular Th cell responses in autoimmune- and SLE-prone mice and protein Ag-immunized and influenza virus-infected mice were intact in the absence of STAT4. Together, our data demonstrate a largely dispensable role for STAT4 in AFC, GC, and Ab responses in SLE mouse models and in certain foreign Ag-driven responses.

Association between systemic lupus erythematosus and lung cancer: results from a pool of cohort studies and Mendelian randomization analysis

Background

Epidemiological evidence suggested that systemic lupus erythematosus (SLE) might be correlated with an increased risk of lung cancer. Nevertheless, few studies have comprehensively investigated their correlation and the causal effect remains unclear. With a meta-analysis and Mendelian randomization (MR) approach, we were able to systematically investigate the relationship between SLE and lung cancer risk.

Methods

A systematic search of cohort studies was conducted using network databases from the inception dates to February 1, 2020. Meta-analysis was performed to calculate standardized incidence rate (SIR) and their 95% CI. Furthermore, utilizing 33 SLE-related single nucleotide polymorphisms as instrumental variables (IVs) identified by the latest genome-wide association studies (GWASs), we investigated the correlation between genetically predisposed SLE and lung cancer risk using summary statistics from the International Lung Cancer Consortium (11,348 cases and 15,861 controls). The Inverse variance-weighted method was applied to estimate the causality and we further evaluated the pleiotropy by means of the weighted median and the MR-Egger regression method. Subgroup analysis according to different histotypes of lung cancer was also conducted.

Results

Through meta-analysis of 15 cohort studies involving 110,519 patients, we observed an increased risk of lung cancer among SLE patients (SIR =1.63, 95% CI, 1.39-1.90). Subgroup analysis suggested that female patients (SIR =1.28, 95% CI, 1.13-1.44) have a relatively higher lung cancer risk compared with male patients (SIR =1.15, 95% CI, 1.02-1.30). MR analysis indicated that genetically predisposed SLE was causally associated with an increased lung cancer risk (OR =1.045, 95% CI, 1.005-1.086, P=0.0276). When results were examined by histotypes, a causal relationship was observed between genetically predisposed SLE and squamous cell lung cancer (OR =1.065, 95% CI, 1.002-1.132, P=0.0429). Additionally, the results demonstrated the absence of the horizontal pleiotropy.

Conclusions

Both meta-analysis and MR analysis results suggested that SLE was associated with an increased lung cancer risk. Further investigations are warranted to investigate the etiology underlying the attribution of SLE to lung cancer.

A Unique Epigenomic Landscape Defines Human Erythropoiesis

Mammalian erythropoiesis yields a highly specialized cell type, the mature erythrocyte, evolved to meet the organismal needs of increased oxygen-carrying capacity. To better understand the regulation of erythropoiesis, we performed genome-wide studies of chromatin accessibility, DNA methylation, and transcriptomics using a recently developed strategy to obtain highly purified populations of primary human erythroid cells. The integration of gene expression, DNA methylation, and chromatin state dynamics reveals that stage-specific gene regulation during erythropoiesis is a stepwise and hierarchical process involving many cis-regulatory elements. Erythroid-specific, nonpromoter sites of chromatin accessibility are linked to erythroid cell phenotypic variation and inherited disease. Comparative analyses of stage-specific chromatin accessibility indicate that there is limited early chromatin priming of erythroid genes during hematopoiesis. The epigenome of terminally differentiating erythroid cells defines a distinct subset of highly specialized cells that are vastly dissimilar from other hematopoietic and nonhematopoietic cell types. These epigenomic and transcriptome data are powerful tools to study human erythropoiesis.

Schulz et al. use genome-wide studies of chromatin accessibility, DNA methylation, and transcriptomes in primary human erythroid cells to reveal important characteristics of erythropoiesis. Chromatin accessibility of terminal erythroid differentiation is markedly dissimilar from other hematopoietic cell types. Epigenomic changes are linked to erythroid cell traits and disease genes.

Meta-analysis of genome-wide association study identifies FBN2 as a novel locus associated with systemic lupus erythematosus in Thai population

BACKGROUND

Differences in the expression of variants across ethnic groups in the systemic lupus erythematosus (SLE) patients have been well documented. However, the genetic architecture in the Thai population has not been thoroughly examined. In this study, we carried out genome-wide association study (GWAS) in the Thai population.

METHODS

Two GWAS cohorts were independently collected and genotyped: discovery dataset (487 SLE cases and 1606 healthy controls) and replication dataset (405 SLE cases and 1590 unrelated disease controls). Data were imputed to the density of the 1000 Genomes Project Phase 3. Association studies were performed based on different genetic models, and pathway enrichment analysis was further examined. In addition, the performance of disease risk estimation for individuals in Thai GWAS was assessed based on the polygenic risk score (PRS) model trained by other Asian populations.

RESULTS

Previous findings on SLE susceptible alleles were well replicated in the two GWAS. The SNPs on HLA class II (rs9270970, A>G, OR = 1.82, p value = 3.61E-26), STAT4 (rs7582694, C>G, OR = 1.57, p value = 8.21E-16), GTF2I (rs73366469, A>G, OR = 1.73, p value = 2.42E-11), and FAM167A-BLK allele (rs13277113, A>G, OR = 0.68, p value = 1.58E-09) were significantly associated with SLE in Thai population. Meta-analysis of the two GWAS identified a novel locus at the FBN2 that was specifically associated with SLE in the Thai population (rs74989671, A>G, OR = 1.54, p value = 1.61E-08). Functional analysis showed that rs74989671 resided in a peak of H3K36me3 derived from CD14+ monocytes and H3K4me1 from T lymphocytes. In addition, we showed that the PRS model trained from the Chinese population could be applied in individuals of Thai ancestry, with the area under the receiver-operator curve (AUC) achieving 0.76 for this predictor.

CONCLUSIONS

We demonstrated the genetic architecture of SLE in the Thai population and identified a novel locus associated with SLE. Also, our study suggested a potential use of the PRS model from the Chinese population to estimate the disease risk for individuals of Thai ancestry.

The application of ubiquitin ligases in the PROTAC drug design

Protein ubiquitylation plays important roles in many biological activities. Protein ubiquitylation is a unique process that is mainly controlled by ubiquitin ligases. The ubiquitin-proteasome system (UPS) is the main process to degrade short-lived and unwanted proteins in eukaryotes. Many components in the UPS are attractive drug targets. Recent studies indicated that ubiquitin ligases can be employed as tools in proteolysis-targeting chimeras (PROTACs) for drug discovery. In this review article, we will discuss the recent progress of the application of ubiquitin ligases in the PROTAC drug design. We will also discuss advantages and existing problems of PROTACs. Moreover, we will propose a few principles for selecting ubiquitin ligases in PROTAC applications.

Genome-wide study of immune biomarkers in cerebrospinal fluid and serum from patients with bipolar disorder and controls

Bipolar disorder is a common, chronic psychiatric disorder. Despite high heritability, there is a paucity of identified genetic risk factors. Immune biomarkers are under more direct genetic influence than bipolar disorder. To explore the genetic associations with immune biomarker levels in cerebrospinal fluid (CSF) and blood serum which previously showed differences in bipolar disorder, we performed a study involving 291 individuals (184 bipolar disorder patients and 107 controls). The biomarkers assayed in both CSF and serum were: chitinase-3-like protein-1 (YKL-40), monocyte chemoattractant protein-1 (MCP-1), soluble cluster of differentiation (sCD14), tissue inhibitor of metalloproteinases-1 and 2 (TIMP-1 and TIMP-2). C-reactive protein (CRP) was only quantified in serum, and interleukin 8 (IL-8) measures were only available in CSF. Genome-wide association studies were conducted using PLINK for each of three genotyping waves and incorporated covariates for population substructure, age, sex, and body mass index (BMI). Results were combined by meta-analysis. Genome-wide significant associations were detected for all biomarkers except TIMP-1 and TIMP-2 in CSF. The strongest association in CSF was found for markers within the CNTNAP5 gene with YKL-40 (rs150248456, P = 2.84 × 10^-10). The strongest association in serum was also for YKL-40 but localized to the FANCI gene (rs188263039, P = 5.80 × 10^-26). This study revealed numerous biologically plausible genetic associations with immune biomarkers in CSF and blood serum. Importantly, the genetic variants regulating immune biomarker levels in CSF and blood serum differ. These results extend our knowledge of how biomarkers showing alterations in bipolar disorder are genetically regulated.

Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis

Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.

Genome Variation and Precision Medicine in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a complex autoimmune disease which is facing the difficulties in treatment. Genetics play an important role in SLE. Several studies have shown that genetic factors not only affect the development of SLE, but also affect its clinical progress. In this review article, we focus on exploring the influence of genetics on different aspects of SLE pathogenesis, clinical course, and treatment and will provide some references in further precision medicine for SLE patients. The coming era of precision medicine, SLE patients will be stratified by genetic profiling. This will enable us to make more effective and precise choices of treatment plan.

Machine learning applied to whole-blood RNA-sequencing data uncovers distinct subsets of patients with systemic lupus erythematosus

Objectives

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease that is difficult to treat. There is currently no optimal stratification of patients with SLE, and thus, responses to available treatments are unpredictable. Here, we developed a new stratification scheme for patients with SLE, based on the computational analysis of patients’ whole‐blood transcriptomes.

Methods

We applied machine learning approaches to RNA‐sequencing (RNA‐seq) data sets to stratify patients with SLE into four distinct clusters based on their gene expression profiles. A meta‐analysis on three recently published whole‐blood RNA‐seq data sets was carried out, and an additional similar data set of 30 patients with SLE and 29 healthy donors was incorporated in this study; a total of 161 patients with SLE and 57 healthy donors were analysed.

Results

Examination of SLE clusters, as opposed to unstratified SLE patients, revealed underappreciated differences in the pattern of expression of disease‐related genes relative to clinical presentation. Moreover, gene signatures correlated with flare activity were successfully identified.

Conclusion

Given that SLE disease heterogeneity is a key challenge hindering the design of optimal clinical trials and the adequate management of patients, our approach opens a new possible avenue addressing this limitation via a greater understanding of SLE heterogeneity in humans. Stratification of patients based on gene expression signatures may be a valuable strategy allowing the identification of separate molecular mechanisms underpinning disease in SLE. Further, this approach may have a use in understanding the variability in responsiveness to therapeutics, thereby improving the design of clinical trials and advancing personalised therapy.

The pathogenesis of systemic lupus erythematosus: Harnessing big data to understand the molecular basis of lupus

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease that causes damage to multiple organ systems. Despite decades of research and available murine models that capture some aspects of the human disease, new treatments for SLE lag behind other autoimmune diseases such as Rheumatoid Arthritis and Crohn's disease. Big data genomic assays have transformed our understanding of SLE by providing important insights into the molecular heterogeneity of this multigenic disease. Gene wide association studies have demonstrated more than 100 risk loci, supporting a model of multiple genetic hits increasing SLE risk in a non-linear fashion, and providing evidence of ancestral diversity in susceptibility loci. Epigenetic studies to determine the role of methylation, acetylation and non-coding RNAs have provided new understanding of the modulation of gene expression in SLE patients and identified new drug targets and biomarkers for SLE. Gene expression profiling has led to a greater understanding of the role of myeloid cells in the pathogenesis of SLE, confirmed roles for T and B cells in SLE, promoted clinical trials based on the prominent interferon signature found in SLE patients, and identified candidate biomarkers and cellular signatures to further drug development and drug repurposing. Gene expression studies are advancing our understanding of the underlying molecular heterogeneity in SLE and providing hope that patient stratification will expedite new therapies based on personal molecular signatures. Although big data analyses present unique interpretation challenges, both computationally and biologically, advances in machine learning applications may facilitate the ability to predict changes in SLE disease activity and optimize therapeutic strategies.

Rare variants in non-coding regulatory regions of the genome that affect gene expression in systemic lupus erythematosus

Personalized medicine approaches are increasingly sought for diseases with a heritable component. Systemic lupus erythematosus (SLE) is the prototypic autoimmune disease resulting from loss of immunologic tolerance, but the genetic basis of SLE remains incompletely understood. Genome wide association studies (GWAS) identify regions associated with disease, based on common single nucleotide polymorphisms (SNPs) within them, but these SNPs may simply be markers in linkage disequilibrium with other, causative mutations. Here we use an hierarchical screening approach for prediction and testing of true functional variants within regions identified in GWAS; this involved bioinformatic identification of putative regulatory elements within close proximity to SLE SNPs, screening those regions for potentially causative mutations by high resolution melt analysis, and functional validation using reporter assays. Using this approach, we screened 15 SLE associated loci in 143 SLE patients, identifying 7 new variants including 5 SNPs and 2 insertions. Reporter assays revealed that the 5 SNPs were functional, altering enhancer activity. One novel variant was linked to the relatively well characterized rs9888739 SNP at the ITGAM locus, and may explain some of the SLE heritability at this site. Our study demonstrates that non-coding regulatory elements can contain private sequence variants affecting gene expression, which may explain part of the heritability of SLE.

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.

Susceptible loci associated with autoimmune disease as potential biomarkers for checkpoint inhibitor-induced immune-related adverse events

Unprecedented successes regarding cancer immunotherapy have been achieved, in which therapeutic agents are used to target immune cells rather than cancer cells. The most effective immunotherapy to date is the group of immune checkpoint inhibitors (CPI), targeting, for example, cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) or programmed cell death protein (PD-1). TThe combination of these therapies (anti-PD-1 with anti-CTLA-4) induces high response rates, and seem to be increased further when applied in early-stage disease. However, combined CTLA-4 plus PD-1 blockade causes frequent high-grade immune-related adverse events (irAE). To date, research on biological mechanism of irAEs is scarce and no widely accepted biomarkers predicting onset of severe irAEs have been identified. The similarity of irAEs to autoimmune disorders fuels the hypothesis that irAEs may be linked to susceptible genetic loci related to various autoimmune diseases. In this review, we extensively searched for susceptible loci associated with various autoimmune diseases, and pooled them in groups most likely to be associated with CPI-induced irAEs. These sets could be used in future research on predicting irAEs and guide physicians in a more refined and personal manner.

SNP rs4937333 in the miRNA-5003-Binding Site of the ETS1 3'-UTR Decreases ETS1 Expression

Mutations in and reduced expression of the ETS1 gene may be associated with systemic lupus erythematosus (SLE). Here, we report a replication study to investigate associations of eight ETS1 single-nucleotide polymorphisms in the 3′-untranslated region (3′-UTR) with SLE and their regulation of ETS1 expression in a study population. We found that the rs4937333 T allele was associated with a significantly increased risk of SLE (odds ratio: 1.800, 95% confidence interval: 1.02–3.157, P = 0.040) and with dramatically reduced levels of ETS1 in B cells from SLE subjects. Functionally, the rs4937333 T allele alters the binding affinity between miR-5003 and its ETS1 3′-UTR target, thus enhancing suppression of ETS1 expression. Furthermore, immunoglobulin M-secreting plasmacytes were significantly reduced among B cells with the rs4937333 C allele versus the T allele according to FACS and ELISA. Additionally, miR-5003 expression was higher in B cells than in T cells from SLE patients, and a negative correlation between miR-5003 and ETS1 was found, especially in B cells with the T allele. These findings suggest that the rs4937333 T allele is a risk factor for susceptibility to SLE in the studied population. The rs4937333 T allele may enhance the binding of miR-5003 to ETS1, which probably promotes the involvement of ETS1 in the differentiation of B cells into plasmacytes.

Type1 Interferons Potential Initiating Factors Linking Skin Wounds With Psoriasis Pathogenesis

Psoriasis is a chronic autoimmune skin disease that can often be triggered upon skin injury, known as Koebner phenomenon. Type 1 interferons (IFNα and IFNβ), key cytokines that activate autoimmunity during viral infection, have been suggested to play an indispensable role in initiating psoriasis during skin injury. Type 1 IFN-inducible gene signature has been identified as one of the major upregulated gene signatures in psoriatic skin. Type 1 IFNs treatments often directly induce or exacerbate psoriasis, whereas blocking type 1 IFNs signaling pathway in animal models effectively inhibits the development of T cell-mediated skin inflammation and psoriasis-like inflammatory diseases. Epidermal keratinocytes (KCs) occupy the outermost position in the skin and are the first responder to skin injury. Skin injury rapidly induces IFNβ from KCs and IFNα from dermal plasmacytoid dendritic cells (pDCs) through distinct mechanisms. Host antimicrobial peptide LL37 potentiates double-stranded RNA (dsRNA) immune pathways in keratinocytes and single-stranded RNA or DNA pathways in pDCs, leading to production of distinct type 1 IFN genes. IFNβ from KC promotes dendritic cell maturation and the subsequent T cell proliferation, contributing to autoimmune activation during skin injury and psoriasis pathogenesis. Accumulating evidences have indicated an important role of this dsRNA immune pathway in psoriasis pathogenesis. Together, this review describes how skin injury induces type 1 IFNs from skin cells and how this may initiate autoimmune cascades that trigger psoriasis. Targeting keratinocytes or type 1 IFNs in combination with T cell therapy may result in more sustainable effect to treat auto-inflammatory skin diseases such as psoriasis.

Management strategies and future directions for systemic lupus erythematosus in adults

Systemic lupus erythematosus (SLE) is an autoimmune disease characterised by the loss of self-tolerance and formation of nuclear autoantigens and immune complexes resulting in inflammation of multiple organs. The clinical presentation of SLE is heterogeneous, can involve one or more organs, including the skin, kidneys, joints, and nervous system, and take a chronic or relapsing and remitting disease course. SLE is most common in women and in those of non-white ethnicity. Because of the multitude of presentations, manifestations, and serological abnormalities in patients with SLE, diagnosis can be challenging. Therapeutic approaches predominantly involve immunomodulation and immunosuppression and are targeted to the specific organ manifestation, with the aim of achieving low disease activity. Despite many treatment advances and improved diagnostics, SLE continues to cause substantial morbidity and premature mortality. Current management strategies, although helpful, are limited by high failure rates and toxicity. An overreliance on corticosteroid therapy contributes to much of the long-term organ damage. In this Seminar, we outline the classification criteria for SLE, current treatment strategies and medications, the evidence supporting their use, and explore potential future therapies.

The Role of Monocytes and Macrophages in Autoimmune Diseases: A Comprehensive Review

Monocytes (Mo) and macrophages (Mϕ) are key components of the innate immune system and are involved in regulation of the initiation, development, and resolution of many inflammatory disorders. In addition, these cells also play important immunoregulatory and tissue-repairing roles to decrease immune reactions and promote tissue regeneration. Several lines of evidence have suggested a causal link between the presence or activation of these cells and the development of autoimmune diseases. In addition, Mo or Mϕ infiltration in diseased tissues is a hallmark of several autoimmune diseases. However, the detailed contributions of these cells, whether they actually initiate disease or perpetuate disease progression, and whether their phenotype and functional alteration are merely epiphenomena are still unclear in many autoimmune diseases. Additionally, little is known about their heterogeneous populations in different autoimmune diseases. Elucidating the relevance of Mo and Mϕ in autoimmune diseases and the associated mechanisms could lead to the identification of more effective therapeutic strategies in the future.

Exploring Impact of Rare Variation in Systemic Lupus Erythematosus by a Genome Wide Imputation Approach

The importance of low frequency and rare variation in complex disease genetics is difficult to estimate in patient populations. Genome-wide association studies are therefore, underpowered to detect rare variation. We have used a combined approach of genome-wide-based imputation with a highly stringent sequence kernel association (SKAT) test and a case-control burden test. We identified 98 candidate genes containing rare variation that in aggregate show association with SLE many of which have recognized immunological function, but also function and expression related to relevant tissues such as the joints, skin, blood or central nervous system. In addition we also find that there is a significant enrichment of genes annotated for disease-causing mutations in the OMIM database, suggesting that in complex diseases such as SLE, such mutations may be involved in subtle or combined phenotypes or could accelerate specific organ abnormalities found in the disease. We here provide an important resource of candidate genes for SLE.

Immune Profiling and Precision Medicine in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disorder with a wide range of clinical symptoms. Enormous progress has been made in the immunological and genetic understanding of SLE. However, the biology of disease heterogeneity in SLE has remained largely unexplored. Human immune profiling studies, helped by recent technological advances especially in single-cell and “omics” analyses, are now shedding light on the cellular and molecular basis of clinical symptoms and disease flares in individual patients. Peripheral blood immunophenotyping analysis with flow cytometry or mass cytometry are identifying responsible cell subsets and markers characteristic of disease heterogeneity. Transcriptome analysis is discovering molecular networks responsible for disease activity, disease subtype and future relapse. In this review, we summarize recent advances in the immune profiling analysis of SLE patients and discuss how they will be used for future precision medicine.

Interleukin 10 gene promoter polymorphisms (rs1800896, rs1800871 and rs1800872) and haplotypes are associated with the activity of systemic lupus erythematosus and IL10 levels in an Iranian population

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with unknown aetiology. According to the role of interleukin 10 (IL10) in SLE pathogenesis, the genetic alterations in its promoter region could be associated with elevated IL10 levels and exacerbated disease. Here, we investigated the association of genotype and haplotype frequencies of three IL10 gene promoter polymorphisms with susceptibility to SLE, IL10 plasma levels and disease activity of patients in an Iranian population. A total of 116 SLE patients and 131 healthy subjects were enrolled. The PCR-RFLP technique was used to detect IL10 promoter genotypes at the positions of -1082 (G/A), -819 (C/T) and -592 (C/A) in association with IL10 plasma levels and SLEDAI scores. The GG genotype of -1082 polymorphism was associated with the increased risk of SLE [OR = 2.65, 95% CI (1.21-5.82), p-value = 0.046]. The CC genotype in -819 region was associated with SLE susceptibility [OR = 3.38, 95% CI (1.26-9.07), p-value = 0.034] and C allele was introduced as risk allele [OR = 1.86, 95% CI (1.15-3.01), p-value = 0.009] in this region. IL10 plasma levels were overexpressed in CC genotype carriers of -592 SNP and decreased in AA genotype carriers of -1082. IL10 was also increased in SLE patients with CGT (-592/-1082/-819) haplotype. The SLEDAI score was higher among CC genotype carriers at the position of -592 and TT genotype carriers at the region of -819. SLEDAI was also elevated among patients with CGC (-592/-1082/-819) and CAC (p = 0.011) haplotypes. The present study suggests that the IL10 -819(C/T), -1082(G/A) and -592(C/A) polymorphisms and the haplotypes are associated with SLE susceptibility, increased disease activity and elevated IL10 levels. While this is the first time to report such an association in an Iranian population, further studies are needed to confirm these findings.