Large-scale meta-analysis across East Asian and European populations updated genetic architecture and variant-driven biology of rheumatoid arthritis, identifying 11 novel susceptibility loci

Enhancer variants on chromosome 2p14 regulating SPRED2 and ACTR2 act as a signal amplifier to protect against rheumatoid arthritis

Genome-wide association studies (GWASs) have repeatedly reported multiple non-coding single-nucleotide polymorphisms (SNPs) at 2p14 associated with rheumatoid arthritis (RA), but their functional roles in the pathological mechanisms of RA remain to be explored. In this study, we integrated a series of bioinformatics and functional experiments and identified three intronic RA SNPs (rs1876518, rs268131, and rs2576923) within active enhancers that can regulate the expression of SPRED2 directly. At the same time, SPRED2 and ACTR2 influence each other as a positive feedback signal amplifier to strengthen the protective role in RA by inhibiting the migration and invasion of rheumatoid fibroblast-like synoviocytes (FLSs). In particular, the transcription factor CEBPB preferentially binds to the rs1876518-T allele to increase the expression of SPRED2 in FLSs. Our findings decipher the molecular mechanisms behind the GWAS signals at 2p14 for RA and emphasize SPRED2 as a potential candidate gene for RA, providing a potential target and direction for precise treatment of RA.

Variation in ERAP2 has opposing effects on severe respiratory infection and autoimmune disease

ERAP2 is an aminopeptidase involved in immunological antigen presentation. Genotype data in human samples from before and after the Black Death, an epidemic due to Yersinia pestis, have marked changes in allele frequency of the single-nucleotide polymorphism (SNP) rs2549794, with the T allele suggested to be deleterious during this period, while ERAP2 is also implicated in autoimmune diseases. This study explored the association between variation at ERAP2 and (1) infection, (2) autoimmune disease, and (3) parental longevity. Genome-wide association studies (GWASs) of these outcomes were identified in contemporary cohorts (UK Biobank, FinnGen, and GenOMICC). Effect estimates were extracted for rs2549794 and rs2248374, a haplotype tagging SNP. Additionally, cis expression and protein quantitative trait loci (QTLs) for ERAP2 were used in Mendelian randomization (MR) analyses. Consistent with decreased survival in the Black Death, the T allele of rs2549794 showed evidence of association with respiratory infection (odds ratio; OR for pneumonia 1.03; 95% CI 1.01-1.05). Effect estimates were larger for more severe phenotypes (OR for critical care admission with pneumonia 1.08; 95% CI 1.02-1.14). In contrast, opposing effects were identified for Crohn disease (OR 0.86; 95% CI 0.82-0.90). This allele was shown to associate with decreased ERAP2 expression and protein levels, independent of haplotype. MR analyses suggest that ERAP2 expression may be mediating disease associations. Decreased ERAP2 expression is associated with severe respiratory infection with an opposing association with autoimmune diseases. These data support the hypothesis of balancing selection at this locus driven by autoimmune and infectious disease.

Connectome and regulatory hubs of CAGE highly active enhancers

Evidence indicates that enhancers are transcriptionally active. Herein, we investigated transcriptionally active enhancers by using cap analysis of gene expression (CAGE) combined with epigenetic marks and chromatin interactions. We identified CAGE-tag highly active (CHA) enhancers as distant regulatory elements with CAGE-tag ≥ 90th percentile and overlapping with H3K27ac peaks (4.5% of enhancers). CHA enhancers were conserved between mouse and man and were independent from super-enhancers in predicting cell identity with lower P-values. CHA enhancers had increased open chromatin and a higher recruitment of cell-specific transcription factors as well as molecules involved in 3D genome interactions. HiChIP analysis of enhancer-promoter looping indicated that CHA enhancers had a higher density of anchor loops when compared to regular enhancers. A subset of CHA enhancers and promoters characterized by a high density of chromatin loops and forming hub regulatory units were connected to the promoter of immediate early response genes, genes involved in cancer and encoding for transcription factors. Promoter of genes within hub CHA regulatory units were less likely to be paused. CHA enhancers were enriched in gene variants associated with autoimmune disorders and had looping with causal candidate genes as revealed by Mendelian randomization. Hence, CHA enhancers form a dense hierarchical network of chromatin interactions between regulatory elements and genes involved in cell identity and disorders.

Genome-wide identification of RNA modification-related single nucleotide polymorphisms associated with rheumatoid arthritis

BACKGROUND

RNA modification plays important roles in many biological processes, such as gene expression control. The aim of this study was to identify single nucleotide polymorphisms related to RNA modification (RNAm-SNPs) for rheumatoid arthritis (RA) as putative functional variants.

METHODS

We examined the association of RNAm-SNPs with RA in summary data from a genome-wide association study of 19,234 RA cases and 61,565 controls. We performed eQTL and pQTL analyses for the RNAm-SNPs to find associated gene expression and protein levels. Furthermore, we examined the associations of gene expression and circulating protein levels with RA using two-sample Mendelian randomization analysis methods.

RESULTS

A total of 160 RNAm-SNPs related to m⁶A, m¹A, A-to-I, m⁷G, m⁵C, m⁵U and m⁶Am modifications were identified to be significantly associated with RA. These RNAm-SNPs were located in 62 protein-coding genes, which were significantly enriched in immune-related pathways. RNAm-SNPs in important RA susceptibility genes, such as PADI2, SPRED2, PLCL2, HLA-A, HLA-B, HLA-DRB1, HLA-DPB1, TRAF1 and TXNDC11, were identified. Most of these RNAm-SNPs showed eQTL effects, and the expression levels of 26 of the modifiable genes (e.g., PADI2, TRAF1, HLA-A, HLA-DRB1, HLA-DPB1 and HLA-B) in blood cells were associated with RA. Circulating protein levels, such as CFB, GZMA, HLA-DQA2, IL21, LRPAP1 and TFF3, were affected by RNAm-SNPs and were associated with RA.

CONCLUSION

The present study identified RNAm-SNPs in the reported RA susceptibility genes and suggested that RNAm-SNPs may affect RA risk by affecting the expression levels of corresponding genes and proteins.

Identification and preliminary validation of synovial tissue-specific genes and their-mediated biological mechanisms in rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease. It is well known that the formation of positive feedback between synovial hyperplasia and inflammatory infiltration is intimately associated with the occurrence and development of RA. However, the exact mechanisms still remain unknown, making the early diagnosis and therapy of RA difficult. This study was designed to identify prospective diagnostic and therapeutic biomarkers, as well as their-mediated biological mechanisms in RA.

METHODS

Three microarray datasets (GSE36700, GSE77298 and GSE153015) and two RNA-sequencing datasets (GSE89408 and GSE112656) of synovial tissues, as well as three other microarray datasets (GSE101193, GSE134087 and GSE94519) of peripheral blood were downloaded for integrated analysis. The differently expressed genes (DEGs) were identified by "limma" package of R software. Then, weight gene co-expression analysis and gene set enrichment analysis were performed to investigate synovial tissue-specific genes and their-mediated biological mechanisms in RA. The expression of candidate genes and their diagnostic value for RA were verified by quantitative real-time PCR and receiver operating characteristic (ROC) curve, respectively. Relevant biological mechanisms were explored through cell proliferation and colony formation assay. The suggestive anti-RA compounds were discovered by CMap analysis.

RESULTS

We identified a total of 266 DEGs, which were mainly enriched in cellular proliferation and migration, infection and inflammatory immune signaling pathways. Bioinformatics analysis and molecular validation revealed 5 synovial tissue-specific genes, which exhibited excellent diagnostic value for RA. The infiltration level of immune cells in RA synovial tissue was significantly higher than that in control individuals. Moreover, preliminary molecular experiments suggested that these characteristic genes may be responsible for the high proliferation potential of RA fibroblast-like synoviocytes (FLSs). Finally, 8 small molecular compounds with anti-RA potential were obtained.

CONCLUSIONS

We have proposed 5 potential diagnostic and therapeutic biomarkers (CDK1, TTK, HMMR, DLGAP5, and SKA3) in synovial tissues that may contribute to the pathogenesis of RA. These findings may shed light on the early diagnosis and therapy of RA.

Deletion mapping of regulatory elements for GATA3 in T cells reveals a distal enhancer involved in allergic diseases

GATA3 is essential for T cell differentiation and is surrounded by genome-wide association study (GWAS) hits for immune traits. Interpretation of these GWAS hits is challenging because gene expression quantitative trait locus (eQTL) studies lack power to detect variants with small effects on gene expression in specific cell types and the genome region containing GATA3 contains dozens of potential regulatory sequences. To map regulatory sequences for GATA3, we performed a high-throughput tiling deletion screen of a 2 Mb genome region in Jurkat T cells. This revealed 23 candidate regulatory sequences, all but one of which is within the same topological-associating domain (TAD) as GATA3. We then performed a lower-throughput deletion screen to precisely map regulatory sequences in primary T helper 2 (Th2) cells. We tested 25 sequences with ∼100 bp deletions and validated five of the strongest hits with independent deletion experiments. Additionally, we fine-mapped GWAS hits for allergic diseases in a distal regulatory element, 1 Mb downstream of GATA3, and identified 14 candidate causal variants. Small deletions spanning the candidate variant rs725861 decreased GATA3 levels in Th2 cells, and luciferase reporter assays showed regulatory differences between its two alleles, suggesting a causal mechanism for this variant in allergic diseases. Our study demonstrates the power of integrating GWAS signals with deletion mapping and identifies critical regulatory sequences for GATA3.

Multitrait genome-wide analyses identify new susceptibility loci and candidate drugs to primary sclerosing cholangitis

Primary sclerosing cholangitis (PSC) is a rare autoimmune bile duct disease that is strongly associated with immune-mediated disorders. In this study, we implemented multitrait joint analyses to genome-wide association summary statistics of PSC and numerous clinical and epidemiological traits to estimate the genetic contribution of each trait and genetic correlations between traits and to identify new lead PSC risk-associated loci. We identified seven new loci that have not been previously reported and one new independent lead variant in the previously reported locus. Functional annotation and fine-mapping nominated several potential susceptibility genes such as MANBA and IRF5. Network-based in silico drug efficacy screening provided candidate agents for further study of pharmacological effect in PSC.

Multi-ancestry and multi-trait genome-wide association meta-analyses inform clinical risk prediction for systemic lupus erythematosus

Systemic lupus erythematosus is a heritable autoimmune disease that predominantly affects young women. To improve our understanding of genetic etiology, we conduct multi-ancestry and multi-trait meta-analysis of genome-wide association studies, encompassing 12 systemic lupus erythematosus cohorts from 3 different ancestries and 10 genetically correlated autoimmune diseases, and identify 16 novel loci. We also perform transcriptome-wide association studies, computational drug repurposing analysis, and cell type enrichment analysis. We discover putative drug classes, including a histone deacetylase inhibitor that could be repurposed to treat lupus. We also identify multiple cell types enriched with putative target genes, such as non-classical monocytes and B cells, which may be targeted for future therapeutics. Using this newly assembled result, we further construct polygenic risk score models and demonstrate that integrating polygenic risk score with clinical lab biomarkers improves the diagnostic accuracy of systemic lupus erythematosus using the Vanderbilt BioVU and Michigan Genomics Initiative biobanks.

Innate and adaptive immune abnormalities underlying autoimmune diseases: the genetic connections

With the exception of an extremely small number of cases caused by single gene mutations, most autoimmune diseases result from the complex interplay between environmental and genetic factors. In a nutshell, etiology of the common autoimmune disorders is unknown in spite of progress elucidating certain effector cells and molecules responsible for pathologies associated with inflammatory and tissue damage. In recent years, population genetics approaches have greatly enriched our knowledge regarding genetic susceptibility of autoimmunity, providing us with a window of opportunities to comprehensively re-examine autoimmunity-associated genes and possible pathways. In this review, we aim to discuss etiology and pathogenesis of common autoimmune disorders from the perspective of human genetics. An overview of the genetic basis of autoimmunity is followed by 3 chapters detailing susceptibility genes involved in innate immunity, adaptive immunity and inflammatory cell death processes respectively. With such attempts, we hope to expand the scope of thinking and bring attention to lesser appreciated molecules and pathways as important contributors of autoimmunity beyond the 'usual suspects' of a limited subset of validated therapeutic targets.

Exome-wide analysis identify multiple variations in olfactory receptor genes (OR12D2 and OR5V1) associated with autism spectrum disorder in Saudi females

Background

Autism Spectrum Disorder (ASD) is a multifactorial, neurodevelopmental disorder, characterized by deficits in communication, restricted and repetitive behaviors. ASD is highly heritable in Saudi Arabia; indecencies of affected individuals are increasing.

Objectives

To identify the most significant genes and SNPs associated with the increased risk of ASD in Saudi females to give an insight for early diagnosis.

Methods

Pilot case-control study mostly emphasized on the significant SNPs and haplotypes contributing to Saudi females with ASD patients (n = 22) compared to controls (n = 51) without ASD. With the use of allelic association analysis tools, 243,345 SNPs were studied systematically and classified according to their significant association. The significant SNPs and their genes were selected for further investigation for mapping of ASD candidate causal variants and functional impact.

Results

In females, five risk SNPs at p ≤ 2.32 × 10^-05 was identified in association with autism. The most significant exonic variants at chromosome 6p22.1 with olfactory receptor genes (OR12D2 and OR5V1) clustered with high linkage disequilibrium through haplotyping analysis. Comparison between highly associated genes (56 genes) of male and female autistic patients with female autistic samples revealed that 39 genes are unique biomarkers for Saudi females with ASD.

Conclusion

Multiple variations in olfactory receptor genes (OR5V1 and OR12D2) and single variations on SPHK1, PLCL2, AKAP9 and LOC107984893 genes are contributing to ASD in females of Arab origin. Accumulation of these multiple predisposed coding SNPs can increase the possibility of developing ASD in Saudi females.

Mendelian randomization study reveals a causal relationship between rheumatoid arthritis and risk for pre-eclampsia

Background

Epidemiological observational studies have investigated the relationship between rheumatoid arthritis(RA) and pre-eclampsia, but no consistent conclusions were obtained due to various limitations. Hence, we conducted a two-sample mendelian randomization analysis to evaluate the potential causal effect of RA on pre-eclampsia.

Methods

Summary-level statistics for RA were derived from a large-scale meta-analysis of datasets of genome-wide association studies(GWAS) which involved 14,361 cases and 43,923 controls. Moreover, summary statistics for pre-eclampsia or eclampsia were sourced from the Finn biobank which contained 3,903 cases and 114,735 controls. The inverse variance weighting (IVW) as well as other four effective methods including MR-Egger, weighted median, weighted mode, and simple mode were applied to deduce the potential causal relationships between RA and pre-eclampsia comprehensively.

Results

The two-sample MR analysis suggested a strong causal relationship between RA and pre-eclampsia[OR,1.05;95%CI, 1.01-1.09;p<0.05]. The OR estimates obtained from the weighted mode[OR,1.09;95%CI,1.03-1.15;p<0.01] and weighted median[OR,1.07;95%CI, 1.01-1.14;p<0.05] were similar to those from the IVW method, but there was no significant association observed in MR Egger and simple mode analysis.

Conclusion

This MR analysis provides evidence of a positive causal association between RA and pre-eclampsia genetically. Our findings highlight the importance of more intensive prenatal care and early intervention among pregnant women with RA to prevent potential adverse obstetric outcomes. Moreover, our study provides clues for risk factor identification and early prediction of pre-eclampsia.

Identification of novel meQTLs strongly associated with rheumatoid arthritis by large-scale epigenome-wide analysis

Rheumatoid arthritis (RA) is highly heritable, and previous studies have suggested that genetic variation may affect susceptibility to RA by altering epigenetic modifications (e.g. DNA methylation). Here we examined how genetic variation influences DNA methylation (DNAm) in RA by integrating individual genetic variation and DNAm data. Epigenome-wide meQTL (methylation quantitative trait loci) analysis was performed on 354 RA patients and 335 controls, scanning 30,101,744 relationships between 62 SNPs and 485,512 DNA methylation sites. Two regulatory relationship pairs (FDR < 0.05) showed very strong associations with RA risk. One was rs10796216-cg00475509, and the DNAm decreased by 0.0168 per addition of allele rs10796216-A. The other was rs6546473-cg13358873, for which a 0.0365 reduction of DNAm at cg13358873 was observed for each addition of allele rs6546473-A, and lower DNAm was found to be significantly associated with RA risk (P = 2.0407e-28). Moreover, both pairs of meQTL showed a strong regulatory relationship only in RA samples, so they can be subsequently considered as risk markers for RA. In conclusion, our integrated analysis of genetic and epigenetic variation suggests that genetic variation may affect the risk of RA by regulating DNA methylation levels. Alterations of DNAm at cg00475509 and cg13358873 loci conferred by rs10796216-A and rs6546473-A allele may suggest a potential risk for RA. Our results deepen our understanding of the genetic and epigenetic mechanisms of RA and provide novel associations that can be further investigated in future studies.

Genetic susceptibility to autoimmunity-Current status and challenges

Autoimmune diseases (ADs) often arise from a combination of genetic and environmental triggers that disrupt the immune system's capability to properly tolerate body self-antigens. Familial studies provided the earliest insights into the risk loci of such diseases, while genome-wide association studies (GWAS) significantly broadened the horizons. A drug targeting a prominent pathological pathway can be applied to multiple indications sharing overlapping mechanisms. Advances in genomic technologies used in genetic studies provide critical insights into future research on gene-environment interactions in autoimmunity. This Review summarizes the history and recent advances in the understanding of genetic susceptibility to ADs and related immune disorders, including coronavirus disease 2019 (COVID-19), and their indications for the development of diagnostic or prognostic markers for translational applications.

FCER1G Gene Hypomethylation in Patients with Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease that, when improperly treated, leads to disability in patients. Various factors that may cause the development and activity of RA are being considered. Epigenetic factors are also receiving increasing attention. In our study, we analyzed the association between FCER1G gene methylation and RA activity. We conducted our study in 50 RA patients and 24 controls. The patients were divided into two groups in terms of high disease activity and remission. Quantitative real-time methylation-specific PCR was used to analyze the methylation status of the investigated genes. We observed that RA patients have lower levels of methylation of the FCER1G gene compared to controls, but we did not find any difference in the methylation status of this gene between patients with high disease activity and remission. The results of this study suggest that FCER1G gene methylation may be a new potential epigenetic marker of RA that is independent of disease activity.

A genome-wide association study for rheumatoid arthritis replicates previous HLA and non-HLA associations in a cohort from South Africa

The complex pathogenesis of rheumatoid arthritis (RA) is not fully understood, with few studies exploring the genomic contribution to RA in patients from Africa. We report a genome-wide association study (GWAS) of South-Eastern Bantu-Speaking South Africans (SEBSSAs) with seropositive RA (n = 531) and population controls (n = 2653). Association testing was performed using PLINK (logistic regression assuming an additive model) with sex, age, smoking and the first three principal components as covariates. The strong association with the Human Leukocyte Antigen (HLA) region, indexed by rs602457 (near HLA-DRB1), was replicated. An additional independent signal in the HLA region represented by the lead SNP rs2523593 (near the HLA-B gene; Conditional P-value = 6.4 × 10-10) was detected. Although none of the non-HLA signals reached genome-wide significance (P < 5 × 10-8), 17 genomic regions showed suggestive association (P < 5 × 10-6). The GWAS replicated two known non-HLA associations with MMEL1 (rs2843401) and ANKRD55 (rs7731626) at a threshold of P < 5 × 10-3 providing, for the first time, evidence for replication of non-HLA signals for RA in sub-Saharan African populations. Meta-analysis with summary statistics from an African-American cohort (CLEAR study) replicated three additional non-HLA signals (rs11571302, rs2558210 and rs2422345 around KRT18P39-NPM1P33, CTLA4-ICOS and AL645568.1, respectively). Analysis based on genomic regions (200 kb windows) further replicated previously reported non-HLA signals around PADI4, CD28 and LIMK1. Although allele frequencies were overall strongly correlated between the SEBSSA and the CLEAR cohort, we observed some differences in effect size estimates for associated loci. The study highlights the need for conducting larger association studies across diverse African populations to inform precision medicine-based approaches for RA in Africa.

Multiomics analysis of rheumatoid arthritis yields sequence variants that have large effects on risk of the seropositive subset

OBJECTIVES

To find causal genes for rheumatoid arthritis (RA) and its seropositive (RF and/or ACPA positive) and seronegative subsets.

METHODS

We performed a genome-wide association study (GWAS) of 31 313 RA cases (68% seropositive) and ~1 million controls from Northwestern Europe. We searched for causal genes outside the HLA-locus through effect on coding, mRNA expression in several tissues and/or levels of plasma proteins (SomaScan) and did network analysis (Qiagen).

RESULTS

We found 25 sequence variants for RA overall, 33 for seropositive and 2 for seronegative RA, altogether 37 sequence variants at 34 non-HLA loci, of which 15 are novel. Genomic, transcriptomic and proteomic analysis of these yielded 25 causal genes in seropositive RA and additional two overall. Most encode proteins in the network of interferon-alpha/beta and IL-12/23 that signal through the JAK/STAT-pathway. Highlighting those with largest effect on seropositive RA, a rare missense variant in STAT4 (rs140675301-A) that is independent of reported non-coding STAT4-variants, increases the risk of seropositive RA 2.27-fold (p=2.1×10^-9), more than the rs2476601-A missense variant in PTPN22 (OR=1.59, p=1.3×10^-160). STAT4 rs140675301-A replaces hydrophilic glutamic acid with hydrophobic valine (Glu128Val) in a conserved, surface-exposed loop. A stop-mutation (rs76428106-C) in FLT3 increases seropositive RA risk (OR=1.35, p=6.6×10^-11). Independent missense variants in TYK2 (rs34536443-C, rs12720356-C, rs35018800-A, latter two novel) associate with decreased risk of seropositive RA (ORs=0.63-0.87, p=10^-9-10^-27) and decreased plasma levels of interferon-alpha/beta receptor 1 that signals through TYK2/JAK1/STAT4.

CONCLUSION

Sequence variants pointing to causal genes in the JAK/STAT pathway have largest effect on seropositive RA, while associations with seronegative RA remain scarce.

Construction and Application of Polygenic Risk Scores in Autoimmune Diseases

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with autoimmune diseases and provided unique mechanistic insights and informed novel treatments. These individual genetic variants on their own typically confer a small effect of disease risk with limited predictive power; however, when aggregated (e.g., via polygenic risk score method), they could provide meaningful risk predictions for a myriad of diseases. In this review, we describe the recent advances in GWAS for autoimmune diseases and the practical application of this knowledge to predict an individual’s susceptibility/severity for autoimmune diseases such as systemic lupus erythematosus (SLE) via the polygenic risk score method. We provide an overview of methods for deriving different polygenic risk scores and discuss the strategies to integrate additional information from correlated traits and diverse ancestries. We further advocate for the need to integrate clinical features (e.g., anti-nuclear antibody status) with genetic profiling to better identify patients at high risk of disease susceptibility/severity even before clinical signs or symptoms develop. We conclude by discussing future challenges and opportunities of applying polygenic risk score methods in clinical care.

A Summary on the Genetics of Systemic Lupus Erythematosus, Rheumatoid Arthritis, Systemic Sclerosis, and Sjögren's Syndrome

Systemic lupus erythematosus, systemic sclerosis, rheumatoid arthritis, and Sjögren's syndrome are four major autoimmune rheumatic diseases characterized by the presence of autoantibodies, caused by a dysregulation of the immune system that leads to a wide variety of clinical manifestations. These conditions present complex etiologies strongly influenced by multiple environmental and genetic factors. The human leukocyte antigen (HLA) region was the first locus identified to be associated and still represents the strongest susceptibility factor for each of these conditions, particularly the HLA class II genes, including DQA1, DQB1, and DRB1, but class I genes have also been associated. Over the last two decades, the genetic component of these disorders has been extensively investigated and hundreds of non-HLA risk genetic variants have been uncovered. Furthermore, it is widely accepted that autoimmune rheumatic diseases share molecular disease pathways, such as the interferon (IFN) type I pathways, which are reflected in a common genetic background. Some examples of well-known pleiotropic loci for autoimmune rheumatic diseases are the HLA region, DNASEL13, TNIP1, and IRF5, among others. The identification of the causal molecular mechanisms behind the genetic associations is still a challenge. However, recent advances have been achieved through mouse models and functional studies of the loci. Here, we provide an updated overview of the genetic architecture underlying these four autoimmune rheumatic diseases, with a special focus on the HLA region.

Loss of Gut Barrier Integrity In Lupus

Systemic Lupus Erythematosus is a complex autoimmune disease and its etiology remains unknown. Increased gut permeability has been reported in lupus patients, yet whether it promotes or results from lupus progression is unclear. Recent studies indicate that an impaired intestinal barrier allows the translocation of bacteria and bacterial components into systemic organs, increasing immune cell activation and autoantibody generation. Indeed, induced gut leakage in a mouse model of lupus enhanced disease characteristics, including the production of anti-dsDNA antibody, serum IL-6 as well as cell apoptosis. Gut microbiota dysbiosis has been suggested to be one of the factors that decreases gut barrier integrity by outgrowing harmful bacteria and their products, or by perturbation of gut immune homeostasis, which in turn affects gut barrier integrity. The restoration of microbial balance eliminates gut leakage in mice, further confirming the role of microbiota in maintaining gut barrier integrity. In this review, we discuss recent advances on the association between microbiota dysbiosis and leaky gut, as well as their influences on the progression of lupus. The modifications on host microbiota and gut integrity may offer insights into the development of new lupus treatment.

Discovery and Functional Characterization of Two Regulatory Variants Underlying Lupus Susceptibility at 2p13.1

Genome-wide association studies have identified 2p13.1 as a prominent susceptibility locus for systemic lupus erythematosus (SLE)—a complex, multisystem autoimmune disease. However, the identity of underlying causal variant (s) and molecular mechanisms for increasing disease susceptibility are poorly understood. Using meta-analysis (cases = 10,252, controls = 21,604) followed by conditional analysis, bioinformatic annotation, and eQTL and 3D-chromatin interaction analyses, we computationally prioritized potential functional variants and subsequently experimentally validated their effects. Ethnicity-specific meta-analysis revealed striking allele frequency differences between Asian and European ancestries, but with similar odds ratios. We identified 20 genome-wide significant (p < 5 × 10−8) variants, and conditional analysis pinpointed two potential functional variants, rs6705628 and rs2272165, likely to explain the association. The two SNPs are near DGUOK, mitochondrial deoxyguanosine kinase, and its associated antisense RNA DGUOK-AS1. Using luciferase reporter gene assays, we found significant cell type- and allele-specific promoter activity at rs6705628 and enhancer activity at rs2272165. This is supported by ChIP-qPCR showing allele-specific binding with three histone marks (H3K27ac, H3K4me3, and H3K4me1), RNA polymerase II (Pol II), transcriptional coactivator p300, CCCTC-binding factor (CTCF), and transcription factor ARID3A. Transcriptome data across 28 immune cell types from Asians showed both SNPs are cell-type-specific but only in B-cells. Splicing QTLs showed strong regulation of DGUOK-AS1. Genotype-specific DGOUK protein levels are supported by Western blots. Promoter capture Hi-C data revealed long-range chromatin interactions between rs2272165 and several nearby promoters, including DGUOK. Taken together, we provide mechanistic insights into how two noncoding variants underlie SLE risk at the 2p13.1 locus.

Lupus enhancer risk variant causes dysregulation of IRF8 through cooperative lncRNA and DNA methylation machinery

Despite strong evidence that human genetic variants affect the expression of many key transcription factors involved in autoimmune diseases, establishing biological links between non-coding risk variants and the gene targets they regulate remains a considerable challenge. Here, we combine genetic, epigenomic, and CRISPR activation approaches to screen for functional variants that regulate IRF8 expression. We demonstrate that the locus containing rs2280381 is a cell-type-specific enhancer for IRF8 that spatially interacts with the IRF8 promoter. Further, rs2280381 mediates IRF8 expression through enhancer RNA AC092723.1, which recruits TET1 to the IRF8 promoter regulating IRF8 expression by affecting methylation levels. The alleles of rs2280381 modulate PU.1 binding and chromatin state to regulate AC092723.1 and IRF8 expression differentially. Our work illustrates an integrative strategy to define functional genetic variants that regulate the expression of critical genes in autoimmune diseases and decipher the mechanisms underlying the dysregulation of IRF8 expression mediated by lupus risk variants.

The synovial and blood monocyte DNA methylomes mirror prognosis, evolution and treatment in early arthritis

Identifying predictive biomarkers at early stages of inflammatory arthritis is crucial for starting appropriate therapies to avoid poor outcomes. Monocytes (MOs) and macrophages, largely associated with arthritis, are contributors and sensors of inflammation through epigenetic modifications. In this study, we investigated associations between clinical features and DNA methylation in blood and synovial fluid (SF) MOs in a prospective cohort of patients with early inflammatory arthritis. DNA methylation profiles of undifferentiated arthritis (UA) blood MOs exhibited marked alterations in comparison with those from healthy donors. We identified additional differences both in blood and SF MOs after comparing patients with UA grouped by their future outcomes, i.e., good versus poor. Patient profiles in subsequent visits revealed a reversion toward a healthy level in both groups, those requiring disease-modifying antirheumatic drugs and those who remitted spontaneously. Changes in disease activity between visits also affected DNA methylation, which was partially concomitant in the SF of UA and in blood MOs of patients with rheumatoid arthritis. Epigenetic similarities between arthritis types allow a common prediction of disease activity. Our results constitute a resource of DNA methylation–based biomarkers of poor prognosis, disease activity, and treatment efficacy for the personalized clinical management of early inflammatory arthritis.

Evaluation of tree-based statistical learning methods for constructing genetic risk scores

Background

Genetic risk scores (GRS) summarize genetic features such as single nucleotide polymorphisms (SNPs) in a single statistic with respect to a given trait. So far, GRS are typically built using generalized linear models or regularized extensions. However, these linear methods are usually not able to incorporate gene-gene interactions or non-linear SNP-response relationships. Tree-based statistical learning methods such as random forests and logic regression may be an alternative to such regularized-regression-based methods and are investigated in this article. Moreover, we consider modifications of random forests and logic regression for the construction of GRS.

Results

In an extensive simulation study and an application to a real data set from a German cohort study, we show that both tree-based approaches can outperform elastic net when constructing GRS for binary traits. Especially a modification of logic regression called logic bagging could induce comparatively high predictive power as measured by the area under the curve and the statistical power. Even when considering no epistatic interaction effects but only marginal genetic effects, the regularized regression method lead in most cases to inferior results.

Conclusions

When constructing GRS, we recommend taking random forests and logic bagging into account, in particular, if it can be assumed that possibly unknown epistasis between SNPs is present. To develop the best possible prediction models, extensive joint hyperparameter optimizations should be conducted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04634-w.

Cohesin-Mediated Chromatin Interactions and Autoimmunity

Proper physiological functioning of any cell type requires ordered chromatin organization. In this context, cohesin complex performs important functions preventing premature separation of sister chromatids after DNA replication. In partnership with CCCTC-binding factor, it ensures insulator activity to organize enhancers and promoters within regulatory chromatin. Homozygous mutations and dysfunction of individual cohesin proteins are embryonically lethal in humans and mice, which limits in vivo research work to embryonic stem cells and progenitors. Conditional alleles of cohesin complex proteins have been generated to investigate their functional roles in greater detail at later developmental stages. Thus, genome regulation enabled by action of cohesin proteins is potentially crucial in lineage cell development, including immune homeostasis. In this review, we provide current knowledge on the role of cohesin complex in leukocyte maturation and adaptive immunity. Conditional knockout and shRNA-mediated inhibition of individual cohesin proteins in mice demonstrated their importance in haematopoiesis, adipogenesis and inflammation. Notably, these effects occur rather through changes in transcriptional gene regulation than through expected cell cycle defects. This positions cohesin at the crossroad of immune pathways including NF-kB, IL-6, and IFNγ signaling. Cohesin proteins emerged as vital regulators at early developmental stages of thymocytes and B cells and after antigen challenge. Human genome-wide association studies are remarkably concordant with these findings and present associations between cohesin and rheumatoid arthritis, multiple sclerosis and HLA-B27 related chronic inflammatory conditions. Furthermore, bioinformatic prediction based on protein-protein interactions reveal a tight connection between the cohesin complex and immune relevant processes supporting the notion that cohesin will unearth new clues in regulation of autoimmunity.

Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data

Rheumatoid arthritis (RA) is an autoimmune and inflammatory disease for which there is a lack of therapeutic options. Genome-wide association studies (GWASs) have identified over 100 genetic loci associated with RA susceptibility; however, the most causal risk genes (RGs) associated with, and molecular mechanism underlying, RA remain unknown. In this study, we collected 95 RA-associated loci from multiple GWASs and detected 87 candidate high-confidence risk genes (HRGs) from these loci via integrated multiomics data (the genome-scale chromosome conformation capture data, enhancer-promoter linkage data, and gene expression data) using the Bayesian integrative risk gene selector (iRIGS). Analysis of these HRGs indicates that these genes were indeed, markedly associated with different aspects of RA. Among these, 36 and 46 HRGs have been reported to be related to RA and autoimmunity, respectively. Meanwhile, most novel HRGs were also involved in the significantly enriched RA-related biological functions and pathways. Furthermore, drug repositioning prediction of the HRGs revealed three potential targets (ERBB2, IL6ST, and MAPK1) and nine possible drugs for RA treatment, of which two IL-6 receptor antagonists (tocilizumab and sarilumab) have been approved for RA treatment and four drugs (trastuzumab, lapatinib, masoprocol, and arsenic trioxide) have been reported to have a high potential to ameliorate RA. In summary, we believe that this study provides new clues for understanding the pathogenesis of RA and is important for research regarding the mechanisms underlying RA and the development of therapeutics for this condition.

Genetics of rheumatoid arthritis

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease involving symmetric joints and is generally characterized by persistent pain, tenderness, and destruction of joints. The vast majority of RA patients produce autoantibodies, and immune cell involvement in disease development is well recognized, as is the contribution of other types of cells in synovial tissue, like fibroblasts. It is known that there are major genetic associations with the HLA locus, while multiple non-HLA genetic variants display relatively low risk of RA. Both HLA and non-HLA associations suggest that the profiles of genetic associations for autoantibody-positive vs. autoantibody-negative RA are different. Several alleles of HLA-DRB1 are associated with high risk for autoantibody-positive RA, with the strongest risk characterized by valine at position 11 of the protein sequence (HLA-DRB1*04 and *10 alleles). There is a strong protective effect for the risk of autoantibody-positive RA associated with HLA-DRB1*13 alleles. Although major genetic associations have been known for several years, understanding of the specific mechanisms in the development of increased risk of RA for these variations is work in progress. Current studies focus on the binding of immune receptors involved in recognition of putative peptides in activation of T cells, as well as investigation of cell signaling mechanisms. At least a part of RA risk could be explained by gene-gene and gene-environment interactions. There are currently more than 150 candidate loci with polymorphisms that associate with RA, mainly related to seropositive disease, and new discoveries are anticipated in the future from investigation of diverse human populations. This new research will help create a strong foundation for the continuing process of integrating genetic, epigenetic, transcriptomic, and proteomic data in studies of RA.

Genetically predicted C-reactive protein mediates the association between rheumatoid arthritis and atlantoaxial subluxation

OBJECTIVE

Investigating the causal relationship between rheumatoid arthritis (RA) and atlantoaxial subluxation (AAS) and identifying and quantifying the role of C-reactive protein (CRP) as a potential mediator.

METHODS

Using summary-level data from a genome-wide association study (GWAS), a two-sample Mendelian randomization (MR) analysis of genetically predicted rheumatoid arthritis (14,361 cases, and 43,923 controls) and AAS (141 cases, 227,388 controls) was performed. Furthermore, we used two-step MR to quantitate the proportion of the effect of c-reactive protein-mediated RA on AAS.

RESULTS

MR analysis identified higher genetically predicted rheumatoid arthritis (primary MR analysis odds ratio (OR) 0.61/SD increase, 95% confidence interval (CI) 1.36-1.90) increased risk of AAS. There was no strong evidence that genetically predicted AAS had an effect on rheumatoid arthritis risk (OR 1.001, 95% CI 0.97-1.03). The proportion of genetically predicted rheumatoid arthritis mediated by C-reactive protein was 3.7% (95%CI 0.1%-7.3%).

CONCLUSION

In conclusion, our study identified a causal relationship between RA and AAS, with a small proportion of the effect mediated by CRP, but a majority of the effect of RA on AAS remains unclear. Further research is needed on additional risk factors as potential mediators. In clinical practice, lesions of the upper cervical spine in RA patients need to be given more attention.

The immunological significance of tumor necrosis factor receptor-associated factors (TRAFs)

The tumor necrosis factor receptor (TNFR)-associated factor (TRAF) family of molecules are intracellular signaling adaptors and control diverse signaling pathways mediated not only by the TNFR superfamily and the Toll-like receptor/interleukin-1 receptor superfamily but also by unconventional cytokine receptors such as IL-6 and IL-17 receptors. There are seven family members, TRAF1 to TRAF7, in mammals. Exaggerated immune responses induced through TRAF signaling downstream of these receptors often lead to inflammatory and autoimmune diseases including rheumatoid arthritis, inflammatory bowel disease, psoriasis and autoinflammatory syndromes, and thus those signals are major targets for therapeutic intervention. For this reason, it has been very important to understand signaling mechanisms regulated by TRAFs that greatly impact on life/death decisions and the activation, differentiation and survival of cells of the innate and adaptive immune systems. Accumulating evidence suggests that dysregulated cellular expression and/or signaling of TRAFs causes overproduction of proinflammatory cytokines, which facilitates aberrant activation of immune cells. In this review, I will explain the structural and functional aspects that are responsible for the cellular activity and disease outcomes of TRAFs, and summarize the findings of recent studies on TRAFs in terms of how individual TRAF family molecules regulates biological and disease processes in the body in both positive and negative ways. This review also discusses how TRAF mutations contribute to human disease.