Genes & Immunity

Epigenetic changes at specific genetic loci and the activation of transcriptional repressor FOXP3 are needed to establish and maintain the regulatory T cell (Treg) lineage. Here we studied the DNA methylation profiles in CD4+ CD25+ Tregs and CD4+ CD25- conventional T cells (Tconvs) from healthy individuals and identified a wide range of differentially methylated CpG sites (DMPs). Overall, Tregs had more hypomethylated DMPs and contained more CpG sites, which on the cell population level were less defined in their methylation status. We identified top hypomethylated CpGs in Tregs close to CENPM, IKZF2, and LYST and hypermethylated sites at the THEMIS, SCML4, and ADD3 genes. Among others, DMPs were enriched for the transcriptional repressor Kaiso binding motifs. Interestingly, in Tregs we found hypomethylation and increased expression of the TSHR gene, which is a risk gene for Graves disease (GD). However, subsequent DNA methylation profiling in healthy individuals and GD patients revealed only 19 DMPs and no change at the TSHR locus, indicating that Tregs in GD patients share a similar methylation pattern with healthy controls. Together, we show Treg-specific hypomethylation and expression of the TSHR gene, prompting additional scenarios to explain the genetic link and role of anti-TSHR autoantibodies in GD.

BackgroundGenetic factors influencing immune response pathways in Andean populations may underlie adaptations to high-altitude environments. To investigate transcriptomic signatures associated with altitude, we analyzed immune-related gene expression across individuals residing at different elevations. MethodsWe recruited 62 Peruvian volunteers, predominantly from rural regions with high proportions of indigenous ancestry, living at low and high altitudes. Peripheral blood mononuclear cells (PBMCs) were stimulated with bacterial lipopolysaccharide (LPS), Pam3CSK4 (a synthetic triacylated lipopeptide), and R848 (an imidazoquinoline analog of viral nucleic acids). Population structure and ancestry were characterized, and transcriptome-wide differential expression analyses were performed. ResultsWe identified 30 genes with significant altitude-associated expression differences, including 22 downregulated (e.g., FN1, CD36, FOS) and nine upregulated genes. Functional enrichment indicated roles in acute inflammatory response, leukocyte migration, and positive regulation of myeloid leukocyte differentiation. ConclusionsHigh- and low-altitude Andean individuals exhibit distinct immune gene expression profiles, defining a population-specific transcriptomic signature that may reflect altitude-related immune adaptation. AUTHOR SUMMARYAndean populations exhibit genetic adaptations in immune response pathways, potentially linked to high-altitude living. To investigate this, we conducted genome-wide and transcriptome-wide analyses to identify immune-related gene expression differences between high- and low-altitude residents. We analyzed the genetic structure and ancestry of Peruvian individuals (primarily rural, with strong indigenous ancestry) living at different altitudes. Peripheral blood mononuclear cells (PBMCs) from 62 volunteers were stimulated with bacterial (LPS, Pam3CSK4) and viral (R848) mimics to assess immune responses. Differential expression analysis identified 22 down-regulated genes (e.g., FN1, CD36, FOS) and nine up-regulated genes, enriched in acute inflammatory response, leukocyte migration, and myeloid leukocyte differentiation. Our findings reveal a unique immune gene expression profile in Andean highlanders, distinct from other populations, suggesting adaptive modulation of both innate and adaptive immunity in response to high-altitude challenges.

HLA loci are highly polymorphic genome regions, with allele frequencies varying significantly across different populations. Population HLA frequency databases may contain biases and make cross-study comparison complicated due to varying data curation protocols, genotyping methodologies, resolution, and inconsistencies in the selection criteria for population samples. This study presents HLA allele frequencies of class I (HLA-A, -B, -C) and class II (HLA-DRB1, -DQB1, -DQA1) as well as their combined haplotypes obtained from over 18,000 whole genome sequencing samples of the Russian population. Cohort was stratified based on PCA and admixture components providing frequencies for 14 different ethnic groups. For 12 groups cohort size allowed us to reach average saturation of 96% of allele frequencies in groups. Moreover, we demonstrated the utility of composed statistics for disease populational study using type 1 diabetes (T1D) as an example. Populations with similar aggregated genetic risk for T1D demonstrated substantial differences in frequencies of risk and protective HLA alleles. Obtained frequency data was made publicly available through the Allele Frequency Net Database improving previously sparse coverage in HLA frequencies data for east Europe and north Asia regions.

Human populations have substantial genetic diversity, but the extent of epigenetic diversity remains unclear, as population-specific DNA methylation (DNAm) has only been studied for [~]3.0% of CpGs. This study quantifies DNAm using whole-genome bisulfite sequencing (WGBS) and analyzes it alongside whole-genome genotype data to reveal a comprehensive picture of population-specific DNAm. Using a "co-methylated region" (CMR) approach, 36,657 CMRs were identified in 62 lymphoblastoid B cell line (LCL) WGBS samples, with validation in array data sets from 326 LCL samples. Between individuals of European and African ancestry, 101 CMRs exhibited population-specific DNAm patterns (Pop-CMRs), including 91 Pop-CMRs not found in previous investigations, which spanned genes (e.g., CCDC42, GYPE, MAP3K20, and OBI1) related to diseases (e.g., malaria infection and diabetes) with different prevalence and incidence rates between populations. Over half of the Pop-CMRs were asscoated with genetic variants, displaying population-specific allele frequencies and primarily mapping to genes involved in metabolic and infectious processes. Additionally, subsets of Pop-CMRs could be applicable in East Asian populations and peripheral blood-based tissues. This study provides insights into DNAm differences across the genome between populations and explores their associations with genetic variants and biological relevance, advancing our understanding of epigenetic roles in population specificity.

ObjectiveGenome-wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) associated with juvenile idiopathic arthritis (JIA), the majority of which are located in non-coding regions such as enhancers. This presents a challenge for pinpointing causal variants and their target genes. Interpreting these loci requires functional genomics data from disease-relevant tissues, which has been lacking for JIA. This study seeks to fill that gap and elucidate the biological mechanisms underlying JIA susceptibility. MethodsWe performed low-input whole genome promoter Capture Hi-C (PCHi-C) and ATAC-seq on CD4+ T cells from three JIA oligoarthritis patients. To link JIA-associated SNPs to potential causal genes, we integrated PCHi-C data with JIA GWAS summary statistics using our Bayesian prioritisation algorithm, Capture Hi-C Omnibus Gene Score (COGS). ATAC-seq was used to further annotate JIA GWAS loci in CD4+ T cells. We then employed CRISPR activation and interference (CRISPRa/i) in Jurkat cells to validate the prioritised SNPs and their corresponding genes. ResultsChromatin interactions between JIA-associated SNPs and gene promoters were identified in 19 of 44 non-MHC JIA loci, linking 61 known and novel target genes to the disease. Through COGS, we prioritised seven putative causal genes for JIA: RGS14, ERAP2, HIPK1, CCR4, CCRL2, CCR2, and CCR3. SNPs within promoter-interacting regions (PIRs) of these genes were further validated using CRISPRa/i to confirm their roles in regulating gene expression. ConclusionsThis study provides insights into the genetic architecture of JIA by integrating genomic and epigenomic data, identifying disease-related genes, functionally validating risk SNPs, and highlighting candidate drugs for repurposing. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSRecent genome-wide association studies in JIA have identified genetic loci associated with disease risk. However, the precise mechanisms by which these variants contribute to disease pathology remain unclear, as most do not directly alter protein-coding genes. It has been proposed that non-coding SNPs can affect genes that are important in disease through disruption of enhancer-mediated regulatory mechanisms that control their expression, with enhancers exerting their effects through chromatin interactions. Functional characterisation of risk loci is essential to delineate causal SNPs and target genes in JIA. What this study addsThis study is the first to utilise low-input Promoter Capture Hi-C to map long-range chromatin interactions in CD4+ T cells from JIA patients, alongside ATAC-seq to assess chromatin accessibility within the same samples. It identifies 61 potential target genes at JIA-associated loci and validates the regulatory roles of some of these through CRISPR activation and interference. This work enhances our understanding of how genetic variants modulate gene expression in immune cells, shedding light on key pathways involved in JIA pathogenesis. How this study might affect research, practice or policyHighlights new potential causal genes in JIA which can help understand the pathological mechanisms in JIA, and suggests the potential to repurpose CCR2/CCR5 inhibitors in JIA.

BackgroundBiologic therapies, such as the IL-4 receptor alpha blocker dupilumab, and Janus kinase (JAK) inhibitors like upadacitinib, have revolutionized the management of atopic dermatitis (AD). However, prolonged treatment is necessary to sustain disease remission. While both therapies are clinically effective, only dupilumab has demonstrated successful dose reduction, suggesting potential disease-modifying effects. This study investigates the immune-modulating potential of one year treatment with dupilumab or upadacitinib in AD by assessing epigenetic and transcriptomic changes in skin-homing T cells. MethodsUsing flow cytometry, CD4+CLA+ T cells were isolated from AD patients (n=12) at baseline and after 52 weeks of dupilumab (n=6) or upadacitinib (n=6) treatment. DNA methylome, RNA transcriptome and cytokines expression analyses were conducted using the EPIC array, RNA sequencing and flow cytometry, respectively. Non-atopic healthy controls (HC) (n=6) were included for comparison. ResultsWe identified 747 differentially methylated regions (DMRs) between HC and AD patients (p-value < 0.1), with a predominance of hypomethylation in AD. These DMR-associated genes were enriched in pathways such as cytokine-cytokine receptor interactions and JAK-STAT signaling. Several DMRs were associated with corresponding changes in the transcriptome and significant differential methylation was observed near 11 AD-associated SNPs. Following treatment, dupilumab partially corrected 6 AD-related DMRs towards the HC profile. Conversely, upadacitinib modulated 40 AD-related DMRs, most shifting further towards the AD profile. Intriguingly, 241 DMRs (upadacitinib) and 13 DMRs (dupilumab) were altered independently of AD-related DMRs, suggesting a broader epigenetic impact of upadacitinib. ConclusionOur findings demonstrate distinct epigenetic effects of dupilumab and upadacitinib in skin-homing T cells from AD patients. The direction and extent of these modifications may contribute to differences in long-term disease control and have clinical implications for therapy discontinuation strategies. Key MessagesO_LISkin-homing T helper cells show unique DNA methylome in AD. C_LIO_LIDupilumab induces targeted DNA methylome changes, partially rectifying some AD-related DMRs. C_LIO_LIUpadacitinib triggers broader DNA methylome changes, augmenting AD-related DMRs and inducing new DMRs. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/650924v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@2e442org.highwire.dtl.DTLVardef@1d7aa16org.highwire.dtl.DTLVardef@1df906corg.highwire.dtl.DTLVardef@82e1fd_HPS_FORMAT_FIGEXP M_FIG C_FIG

There is an established yet unexplained link between interferon (IFN) and systemic lupus erythematosus (SLE). The expression of sequences derived from transposable elements (TEs) may contribute to production of type I IFNs and generation of autoantibodies. We profiled cell-sorted RNA-seq data (CD4+ T cells, CD14+ monocytes, CD19+ B cells, and NK cells) from PBMCs of 120 SLE patients and quantified TE expression identifying 27,135 TEs. We tested for differential TE expression across 10 SLE phenotypes including autoantibody production and disease activity and discovered 731 differentially expressed (DE) TEs whose effects were mostly cell-specific and phenotype-specific. DE TEs were enriched for specific families and viral genes encoded in TE sequences. Increased expression of DE TEs was associated with genes involved in antiviral activity such as LY6E, ISG15, TRIM22 and pathways such as interferon signaling. These findings suggest that expression of TEs contributes to activation of SLE-related mechanisms in a cell-specific manner, which can impact disease diagnostics and therapeutics.

The validation of genome-wide association signals for tuberculosis (TB) susceptibility and the development of type 2 diabetes (T2D) across diverse populations remain problematic. The ancestry-specific variants (coding and non-coding) that contribute to previously identified differentially expressed genes (DEG) in patients with TB, T2D and comorbid TB-T2D, remain unknown. Identifying ancestry-specific expression quantitative trait loci (eQTLs) can aid in distinguishing the most probable disease-causing variants for population-specific therapeutic interventions. Therefore, this study conducted cis-eQTL mapping in TB, T2D and TB-T2D patients to identify variants associated with DEG. Both genotyping (Infinium H3A array with [~]2.3 M markers) and RNA sequencing data of 96 complex multi-way admixed South Africans were used for this purpose. Importantly, both global-and local ancestry adjustment were included in statistical analysis to account for complex admixture. Unique gene-variant pairs were associated with TB-T2D on chromosome 7p22 whilst adjusting for Bantu-speaking African ancestry (PRKAR1B:rs4464850; P=7.68e-07) and Khoe-San ancestry (PRKAR1B:rs117842122; P=3.66e-07). In addition, IFITM3 (a biomarker for the development of TB) was associated with three SNPs (rs11025530, rs3808990, and rs10896664) on chromosome 11p15 while adjusting for Khoe-San ancestry. Our results also indicated that the upregulation of the NLRP6 inflammasome is strongly associated with people with TB-T2D while adjusting for Khoe-San ancestry. Three African-specific eGenes (NLRP6, IFITM3 and PRKAR1B) would have been missed if local ancestry adjustment was not conducted. This study determined a list of ancestry-specific eQTLs in TB-T2D patients that could potentially guide the search for new therapeutic targets for TB-T2D in African populations. Author SummaryThe limitation of genome-wide association study (GWAS) is that the particular biological pathway impacted by a variant might not be evident. eQTL mapping can be conducted to determine the impact that a genetic variant might have on the expression of a specific gene in a biological pathway. In this study the use of cis-eQTL mapping was explored to elucidate the underlying genetic variants that regulate gene expression between TB-T2D and T2D patients, and between TB patients and healthy controls with multi-way genetic admixture from South Africa. Using RNA sequencing data and newly genotyped dataset of 96 individuals (Illumina Infinium H3Africa array with [~]2.5 M markers), we were able to identify ancestry-specific eQTLs. eQTLs of indigenous Khoe-San ancestral origin were identified in genetic regions previously implicated in TB and T2D in African populations. If local ancestry was not incorporated in the cis-eQTL mapping analysis these important African-specific eQTLs would have been missed. Our results provide a list of possible ancestry-specific causal variants associated with TB-T2 comorbidity that could guide the search for new therapeutic targets for African-specific populations. Including populations with complex ancestry and admixture in genetic studies is necessary to improve the quality of genetic research in sub-Saharan African groups.

The genome-wide association studies (GWAS) have identified hundreds of susceptibility loci associated with autoimmune diseases. However, over 90% of risk variants are located in the noncoding regions, leading to great challenges in deciphering the underlying causal functional variants/genes and biological mechanisms. Previous studies focused on developing new scoring method to prioritize functional/disease-relevant variants. However, they principally incorporated annotation data across all cells/tissues while omitted the cell-specific or context-specific regulation. Moreover, limited analyses were performed to dissect the detailed molecular regulatory circuits linking functional GWAS variants to disease etiology. Here we devised a new analysis frame that incorporate hundreds of immune cell-specific multi-omics data to prioritize functional noncoding susceptibility SNPs with gene targets and further dissect their downstream molecular mechanisms and clinical applications for 19 autoimmune diseases. Most prioritized SNPs have genetic associations with transcription factors (TFs) binding, histone modification or chromatin accessibility, indicating their allelic regulatory roles on target genes. Their target genes were significantly enriched in immunologically related pathways and other immunologically related functions. We also detected long-range regulation on 90.7% of target genes including 132 ones exclusively regulated by distal SNPs (eg, CD28, IL2RA), which involves several potential key TFs (eg, CTCF), suggesting the important roles of long-range chromatin interaction in autoimmune diseases. Moreover, we identified hundreds of known or predicted druggable genes, and predicted some new potential drug targets for several autoimmune diseases, including two genes (NFKB1, SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. In summary, our analyses may provide unique resource for future functional follow-up and drug application on autoimmune diseases, which are freely available at http://fngwas.online/. Author SummaryAutoimmune diseases are groups of complex immune system disorders with high prevalence rates and high heritabilities. Previous studies have unraveled thousands of SNPs associated with different autoimmune diseases. However, it remains largely unknown on the molecular mechanisms underlying these genetic associations. Striking, over 90% of risk SNPs are located in the noncoding region. By leveraging multiple immune cell-specific multi-omics data across genomic, epigenetic, transcriptomic and 3D chromatin interaction information, we systematically analyzed the functional variants/genes and biological mechanisms underlying genetic association on 19 autoimmune diseases. We found that most functional SNPs may affect target gene expression through altering transcription factors (TFs) binding, histone modification or chromatin accessibility. Most target genes had known immunological functions. We detected prevailing long-range chromatin interaction linking distal functional SNPs to target genes. We also identified many known drug targets and predicted some new drug target genes for several autoimmune diseases, suggesting their potential clinical applications. All analysis results and tools are available online, which may provide unique resource for future functional follow-up and drug application. Our study may help reduce the gap between traditional genetic findings and biological mechanistically exploration of disease etiologies as well as clinical drug development.

The abundant macrophage population of the intestinal lamina propria turns over rapidly and is replaced by blood monocytes. The differentiation and survival of resident intestinal macrophages depends upon signals from the macrophage colony-stimulating factor receptor (CSF1R). The response of human monocyte-derived macrophages (MDM) grown in macrophage colony-stimulating factor (CSF1) to bacterial lipopolysaccharide (LPS) has been proposed as a model for the differentiation and adaptation of monocytes entering the intestinal lamina propria. We hypothesized that dysregulation of this response leads to susceptibility to chronic inflammatory bowel disease (IBD). To address this hypothesis we analyzed transcriptomic variation in MDM from affected and unaffected sib pairs/trios from 22 IBD families and 6 healthy controls. There was no overall or inter-sib distinction between affected and unaffected individuals in basal gene expression or the stereotypical time course of the response to LPS. However, the basal or LPS-inducible expression of individual genes including inflammatory cytokines and many associated with IBD susceptibility in genome-wide association studies (GWAS) varied by as much as 100-fold between subjects. Extreme independent variation in the expression of pairs of HLA-associated transcripts (HLA-B/C, HLA-A/F and HLA-DRB1/DRB5) was associated with HLA genotype providing a novel explanation for the HLA association with disease susceptibility. The relationship between single nucleotide variant (SNV) genotype and gene expression at other loci was weaker and inconsistent suggesting that much of the variation arises from the integration of multiple trans-acting effects. For example, expression of IL1B at 2 hrs of LPS treatment was significantly associated with local SNV genotype and with peak expression of IL23A at 7 hrs. By contrast, there was no evidence of association between peak IL6 mRNA at 7hrs, IL6-associated SNV genotype or IL1B at 2 hrs. Our results support the view that gene-specific dysregulation in macrophage adaptation to the intestinal milieu provides a plausible explanation for genetic susceptibility to IBD. The analysis also suggests that the molecular basis of susceptibility is unique to each individual which may contribute to variation in the precise environmental trigger, the consequent pathology and response to treatment. Author summaryCells of the innate immune system called macrophages are abundant in the wall of the gut, providing a first line of defense against potential pathogens. These cells must also avoid an inappropriate or excessive response to the abundant microbial population (the microbiome) of the intestine. We have previously proposed that genetic differences between individuals in macrophage adaptation to the unique environment of the intestine underlie genetic susceptibility to inflammatory bowel disease (IBD). In this study we developed a model of the adaptation of macrophages and used that model to identify surprisingly extreme variation in the response amongst a cohort of affected and unaffected siblings in families with IBD. The response did not distinguish affected individuals from their unaffected siblings. Our results support the view that each individual within IBD-susceptible families carries a unique set of genetic variants of large effect that together predispose to uncontrolled gut inflammation in the face of an environmental trigger.

Background and AimsCeliac disease (CeD) is a chronic digestive autoimmune disorder affecting approximately 1% of the worldwide population. It is driven by T cells activated by specific HLA-DQ2 or HLA-DQ8 molecules leading to the destruction of intestinal villi. We aimed to characterize shared CeD-specific T cells in patients on and off a gluten-free diet (GFD) from a large cohort of cases and controls. MethodsWe performed bulk TCR{beta} immune sequencing of the peripheral blood of 1,604 biopsy-confirmed CeD patients (1,339 on GFD, 265 on normal diet) and 1,100 controls. We identified over 300 TCR{beta}s enriched in CeD cases versus controls in an HLA-aware manner, controlling for CeD risk alleles. ResultsCeD-associated TCR{beta}s were found to be more predictive of disease than previously characterized gliadin and glutenin-binding TCRs in a validation cohort. Furthermore, the clonal breadth of these TCR{beta}s was associated with increased intestinal damage. Immune sequencing of the peripheral blood also uncovered repertoire-level differences between CeD patients and controls. CeD patients displayed significantly higher productive clonality compared to age-matched controls as well as expansion of TCR{beta}s specific to cytomegalovirus (CMV) and Epstein-Barr Virus (EBV). ConclusionsThese findings underscore the value of unbiased immune repertoire sequencing to identify novel biomarkers for autoimmune disease and to discover new disease mechanisms which can improve both diagnosis and treatment of disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to a wide-range of clinical outcomes, which have been extensively studied through genome-wide association studies (GWAS). Starting from lead genetic variants associated with COVID-19 infection and severity, we identified a subset of non-coding candidate variants with potential regulatory functions. Using bioinformatics analysis and functional screening in three cell lines, we prioritized two DPP9 variants within a haplotype that increases the risk of severe COVID-19. This haplotype exhibited increased regulatory activity and altered transcription factor binding, suggesting its role in influencing COVID-19 severity through modulation of DPP9 expression in immune and lung cell types. The interest of our study lies in the functional characterization of regulatory variants responsible for the higher levels of DPP9 and lung damage observed in patients with severe COVID-19. These findings advance our understanding of genetic risk factors for COVID-19 and highlight functional SNPs that may guide future therapeutic research.

IntroductionAlthough genome-wide association studies (GWAS) multiple regions conferring genetic risk for juvenile idiopathic arthritis (JIA), we are still faced with the task of identifying the single nucleotide polymorphisms (SNPs) on the disease haplotypes that exert the biological effects that confer risk. Until we identify the risk-driving variants, identifying the genes influenced by these variants, and therefore translating genetic information to improved clinical care, will remain an insurmountable task. We used a function-based approach for identifying causal variant candidates and the target genes on JIA risk haplotypes. MethodsWe used a massively parallel reporter assay (MPRA) in myeloid K562 cells to query the effects of 5,226 SNPs in non-coding regions on JIA risk haplotypes for their ability to alter gene expression when compared to the common allele. The assay relies on 180 bp oligonucleotide reporters ("oligos") in which the allele of interest is flanked by its cognate genomic sequence. Barcodes were added randomly by PCR to each oligo to achieve >20 barcodes per oligo to provide a quantitative read-out of gene expression for each allele. Assays were performed in both unstimulated K562 cells and cells stimulated overnight with interferon gamma (IFNg). As proof of concept, we then used CRISPRi to demonstrate the feasibility of identifying the genes regulated by enhancers harboring expression-altering SNPs. ResultsWe identified 553 expression-altering SNPs in unstimulated K562 cells and an additional 490 in cells stimulated with IFNg. We further filtered the SNPs to identify those plausibly situated within functional chromatin, using open chromatin and H3K27ac ChIPseq peaks in unstimulated cells and open chromatin plus H3K4me1 in stimulated cells. These procedures yielded 42 unique SNPs (total = 84) for each set. Using CRISPRi, we demonstrated that enhancers harboring MPRA-screened variants in the TRAF1 and LNPEP/ERAP2 loci regulated multiple genes, suggesting complex influences of disease-driving variants. ConclusionUsing MPRA and CRISPRi, JIA risk haplotypes can be queried to identify plausible candidates for disease-driving variants. Once these candidate variants are identified, target genes can be identified using CRISPRi informed by the 3D chromatin structures that encompass the risk haplotypes.

Systemic Lupus Erythematosus (SLE) is an autoimmune disease characterized by systemic inflammation involving various immune cell types. Monocytes, pivotal in promoting and regulating inflammation in SLE, differentiate from classical monocytes into intermediate monocytes and non-classical monocytes, assuming diverse roles. In this study, we investigated the epigenetic and transcriptomic profiles of these three monocyte subsets in an SLE cohort. In addition to common DNA methylation and transcriptomic alterations, we identified monocyte subset-specific alterations, especially in DNA methylation, which reflect an impact of SLE on the monocyte differentiation process. SLE classical monocytes exhibited a stronger proinflammatory profile, with an interferon signature and were primed for macrophage differentiation. SLE non-classical monocytes displayed a phenotype related to T cell differentiation regulation, and a Th17-promoting phenotype. Changes in monocyte proportions, DNA methylation and expression occurred in relation to disease activity and involved the STAT1 pathway. Integrating bulk datasets with single-cell RNA-seq data of SLE patients further supported the interferon signature in classical monocytes, associating intermediate and non-classical populations with exacerbated complement activation pathways. Our results indicate a subversion of the epigenome and transcriptome in monocyte differentiation toward non-classical subsets in SLE, impacting function, in relation to disease activity and progression.

IntroductionGWAS have identified multiple regions that confer risk for juvenile idiopathic arthritis (JIA). However, identifying the single nucleotide polymorphisms (SNPs) that drive disease risk is impeded by the SNPs that identify risk loci being in linkage disequilibrium (LD) with hundreds of other SNPs. Since the causal SNPs remain unknown, it is difficult to identify target genes and use genetic information to inform patient care. We used genotyping and functional data in primary human monocytes/macrophages to nominate disease-driving SNPs on JIA risk haplotypes and identify their likely target genes. MethodsWe identified JIA risk haplotypes using Immunochip data from Hinks et al (Nature Gen 2013) and the meta-analysis from McIntosh et al (Arthritis Rheum 2017). We used genotyping data from 3,939 children with JIA and 14,412 healthy controls to identify SNPs that: (1) were situated within open chromatin in multiple immune cell types and (2) were more common in children with JIA than the controls (p< 0.05). We intersected the chosen SNPs (n=846) with regions of bi-directional transcription initiation characteristic of non-coding regulatory regions detected using dREG to analyze GRO-seq data. Finally, we used MicroC data to identify gene promoters interacting with the regulatory regions harboring the candidate causal SNPs. ResultsWe identified 190 SNPs that overlap with dREG peaks in monocytes and126 SNPs that overlap with dREG peaks in macrophages. Of these SNPs, 101 were situated within dREG peaks in both monocytes and macrophages, suggesting that these SNPs exert their effects independent of the cellular activation state. MicroC data in monocytes identified 20 genes/transcripts whose promoters interact with the enhancers harboring the SNPs of interest. ConclusionSNPs in JIA risk regions that are candidate causal variants can be further screened using functional data such as GRO-seq. This process identifies a finite number of candidate causal SNPs, the majority of which are likely to exert their biological effects independent of cellular activation state in monocytes. Three-dimensional chromatin data generated with MicroC identifies genes likely to be influenced by these SNPs. These studies demonstrate the importance of investigations into the role of innate immunity in JIA.

The SNP rs12459419 in exon 2 of the CD33 gene alters mRNA splicing, influencing the expression of a truncated isoform lacking the IgV domain. This isoform enhances amyloid-beta clearance by microglia and is associated with a reduced risk of Alzheimers disease (AD). In this study, we integrate transcriptomic, genomic, epigenomic, and population genetics data to test the hypothesis that rs12459419 regulates CD33 expression in a genotype-dependent manner. We leveraged public datasets including GTEx, 1000 Genomes, ENCODE, and UCSC Genome Browser. Our findings indicate that the T allele of rs12459419 is significantly associated with decreased CD33 expression in microglia-rich tissues, occurs within an accessible chromatin region marked by active histone modifications, and varies in frequency across global populations. These results support a regulatory role for rs12459419 in microglial gene expression with implications for AD pathogenesis and precision medicine.

ObjectivesGiant cell arteritis (GCA) is a large-vessel vasculitis, potentially causing complications such as blindness and strokes. This study aims to gain insights into the pathogenesis of GCA by identifying specific DNA methylation signatures in the arterial tissue of patients with this vasculitis. MethodsDNA methylation profiling was analyzed in 79 temporal artery biopsy samples (69 patients with GCA and 10 controls) by performing an epigenome-wide association study (EWAS). Differential analysis was performed to identify differentially methylated positions (DMPs) and regions (DMRs). Lastly, we compared our findings with previous transcriptomics and epigenomics studies on GCA-affected arteries. ResultsEWAS identified 3,644 DMPs (FDR < 0.05, |{Delta}{beta}| > 0.3), indicating a profound alteration within GCA-affected arterial tissue. These DMPs were annotated to 1,517 potentially dysregulated genes. 282 additional genes were identified by annotation of significant DMRs. Pathway enrichment analysis revealed a significant alteration of inflammatory mechanisms, such as interleukins 2 and 7, as well as pathways related to vascular remodeling. Omics study comparison revealed 37 genes consistently affected across datasets, many of them linked to immune signaling and T cell regulation. Notably, markers of exhausted T cells, including SLAMF6 and HAVCR2, were present among them. ConclusionsOur study identified GCA-specific DNA methylation signatures in arterial tissue, revealing disrupted inflammatory and vascular pathways, and suggesting the involvement of exhausted T cells in this condition. These findings offer new insights into GCA pathogenesis and provide new potential targets for the treatment of this debilitating disease. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABS{square} Affected arteries by giant cell arteritis (GCA) exhibit unique epigenetic signatures, reflecting significant disruptions in gene regulation. However, small sample sizes have constrained the clinical translation and broader interpretation of these findings, leaving key gaps in understanding GCA pathogenesis and identifying therapeutic targets. What this study adds{square} This study provides the largest-to-date epigenome-wide DNA methylation profiling in GCA-affected arteries, uncovering thousands of epigenetic changes and revealing profound disruptions in inflammatory and vascular pathways, including IL-2, IL-7, and CXCR4 signaling. {square}We compiled 37 genes consistently affected across different omics datasets in GCA-affected arteries, providing a robust list of candidates for further research into GCA pathogenesis and treatment. {square}Our findings provide evidence of T cell exhaustion in GCA-affected arteries, supported by consistent changes in key markers such as SLAMF6 and HAVCR2 (TIM-3), suggesting a novel mechanism of immune dysregulation in GCA. How this study might affect research, practice or policy{square} This study nominates exhausted T cells, the NLRP3 inflammasome, and CXCR4 signaling as novel contributors in GCA pathogenesis, suggesting new therapeutic targets for further research in the treatment of this disease.

BackgroundSystemic lupus erythematosus (SLE) is a spontaneous systemic auto-immune condition for which the inciting factors and genetic basis are generally unknown. Although heterogeneous in its manifestations and severity, SLE involves chronic inflammation along with sustained autoantibody production. The root causes and pathophysiology of the inflammation and breaches of tolerance are incompletely understood, but neutrophils are thought to be important elements of the pathophysiology. Type I interferons (IFN) in the bloodstream and an IFN-stimulated gene (ISG) signature in circulating leukocytes, including neutrophils, are common features in many patients. Earlier work has provided evidence of increased levels of transcripts derived from transposable elements (TEs) in peripheral blood cells of SLE patients. Using six leukocyte types, including neutrophils, we tested the correlation of TE expression with disease severity and explored the relationships between increased ISG and TE expression with attention to the genomic locations of the expressed TEs. ResultsWe reanalysed previously published data from neutrophils and other leukocytes of SLE patients sub-divided into ISG-high (termed IFNpos, n=12) and ISG-low (termed IFNneg, n=11) patients in the original study, examining RNA-seq data from B and T lymphocytes, conventional and plasmacytoid dendritic cells (DC), monocytes and PMN of IFNpos and IFNneg SLE patients compared to healthy controls. SLE patients pre-stratified as IFNneg showed no significant increase in TE expression. All IFNpos cell types had similar amounts of total TE-encoded RNA, but among the 6 cell types, PMN had the highest number of differentially expressed TEs and ISGs in IFNpos SLE patients compared to healthy controls. There was a strong correlation between expression of several specific TE families and disease activity assessed at the time of the visit. Most upregulated TEs ([~]80%) were present in introns of upregulated genes, and [~]67% of these were ISGs. By mapping expressed TEs in ISGs, we found that high intronic TE expression correlated strongly with increased ISG expression as well as with splicing alterations in annotated exons flanking expressed TEs. Consistent with autonomous TE expression, upregulated TEs were also observed at intergenic sites distant from annotated genes, perhaps due to weakening of heterochromatin integrity. ConclusionsOur findings show a strong association and suggest mechanistic relationships between increased TE expression and IFN responses in multiple types of leukocytes centrally involved in SLE pathogenesis. Although limited by short-read RNA-seq technology, our analyses support selective upregulation of some TEs independent from the regulation of conventional genes, concurrent with many intron-localized TEs whose expression tracks with ISGs. The data emphasize the need for long-reads sequencing to understand the causes and consequences of high TE expression in SLE and other autoimmune/inflammatory disorders. Important questions include whether TE expression in introns of ISGs and other genes is independently regulated or reflects exonization or partial intron retention, and how frequently it correlates with splicing variations in adjacent exons.

Human leukocyte antigen (HLA) genes play a crucial role in the adaptation of human populations to the dynamic pathogenic environment. Despite their significance, investigating the pathogen-driven evolution of HLAs and the implications for autoimmune diseases presents considerable challenges. Here, we genotyped over twenty HLA genes at 3-field resolution in 8278 individuals from diverse ethnic backgrounds, including 4013 unrelated Han Chinese. We focused on the adaptation of HLAs in the Han Chinese by analysing their binding affinity for various pathogens, and explored the potential correlations between pathogen adaptation and autoimmune diseases. Our findings reveal that specific HLA alleles like HLA-DRB1*07:01 and HLA-DQB1*06:01, confer strong pathogen adaptability at the sequence level, notably for Corynebacterium diphtheriae and Bordetella pertussis. Additionally, alleles like HLA*03:02 demonstrate adaptive selection against pathogens like Mycobacterium tuberculosis and Coronavirus at the gene expression level. Simultaneously, the aforementioned HLA alleles are closely related to some autoimmune diseases such as multiple sclerosis (MS). These exploratory discoveries shed light on the intricate coevolutionary relationships between pathogen adaptation and autoimmune diseases in the human population. These efforts led to an HLA database at http://bigdata.ibp.ac.cn/HLAtyping, aiding searches for HLA allele frequencies (AF) across populations.

ObjectivesWe adopt a weighted variant burden score GenePy2.0 for the UK Biobank phase 2 cohort of inflammatory bowel disease (IBD), to explore potential genomic biomarkers underpinning IBDs known associations. DesignNucleating from IBD GWAS signals, we identified 794 GWAS loci, including target genes/LD-blocks (LDBs) based on linkage-disequilibrium (LD) and functional mapping. We calculated GenePy2.0-a burden score of target regions integrating variants with CADDPhred>15 weighted by deleteriousness and zygosity. Collating with other burden-based test, GenePy-based Mann-Whitney-U tests on cases/controls with varying extreme scores were used. Significance-levels and effect sizes were used for tuning the optimal GenePy thresholds for discriminating patients from controls. Individuals binarized GenePy status (above or below threshold) of candidate regions, was subject to itemset association test via the sparse Apriori algorithm. ResultsA tailored IBD cohort was curated (nCrohns_Disease(CD)=891, nUlcerative_Colitis(UC)=1409, nControls=60118). Analysing 885 unified target regions (794 GWAS loci and 104 monogenic genes with 13 overlaps), the GenePy approach detected statistical significance (permutation p<5.65x10-5) in 35 regions of CD and 25 of UC targets exerting risk and protective effects on the disease. Large effect sizes were observed, e.g. CYLD-AS1 (Mann-Whitney-{square}=0.89[CI:0.78-0.96]) in CD/controls with the top 1% highest scores of the gene. Itemset association learning further highlighted an intriguing signal whereby GenePy status of IL23R and NOD2 were mutually exclusive in CD but always co-occurring in controls. ConclusionGenePy score per IBD patient detected deleterious variation of large effect underpinning known IBD associations and proved itself a promising tool for genomic biomarker discovery. What is already known on this topicInflammatory bowel disease (IBD) is a genetically heterogeneous disease with both common polygenic, and rare monogenic, presentations. Previous studies have identified known genetic variants associated with disease. What this study addsA genomic biomarker tool, tailored for large cohort, GenePy2.0 is developed. Its rank-based test is more powerful than mutation-burden based test in validating known associations and finding new associations of IBD. We identified large risk and protective effects of pathogenic genes/loci in IBD, including expanding previous associations to wider genomic regions. How this study might affect research, practice or policyGenePy2.0 facilitates analysis of diseases with genetic heterogeneity and facilitates personalised genomic analysis on patients. The revealed genetic landscape of IBD captures both risk and protective effects of rare pathogenic variants, alongside more common variation. This, could provide a fresh angle for future targeted therapies in specific groups of patients.