IFI44L promoter methylation as a blood biomarker for systemic lupus erythematosus

A Distinguishable Peripheral Blood and Conjunctival Transcriptome and Gut Microbiome in Sjögren's Disease: A Pilot Study

OBJECTIVE

To create a comprehensive multi-tissue molecular atlas of Sjögren's disease by using unbiased RNA sequencing to identify differentially expressed genes (DEGs) in peripheral blood and conjunctival transcriptomes, and to characterize the ocular surface and gut microbiome profiles in participants classified as Sjögren's versus non-Sjögren's disease.

METHODS

This exploratory study used high-throughput RNA sequencing to analyze peripheral blood, conjunctival swabs, and rectal swabs from participants (11 classified as Sjögren's disease and four classified as non-Sjögren's) to identify DEGs and microbial profiles that could distinguish these groups.

RESULTS

Differential gene expression analysis revealed upregulated type I interferon (IFI44L, OASL, USP18) and complement pathways (SERPING1) in peripheral blood, alongside activation of several novel pathways in the conjunctiva including intracellular vesicle trafficking (HIP1, GOLIM4, FIG4), immunometabolism (CERS5, HPRT1, ULK2), and cytoskeletal remodeling (MARK1, IQCB1) in Sjögren's disease. In addition, distinct gut microbiome compositions were observed in Sjögren's disease participants, characterized by an increased presence of Lactobacillus reuteri species.

CONCLUSIONS

Using unbiased RNA sequencing, we confirmed the role of type I interferon and complement pathways in the peripheral blood and identified novel molecular signatures in the conjunctiva of Sjögren's disease participants. These newly identified pathways-involved in intracellular vesicle trafficking, immunometabolism, and cytoskeletal remodeling-expand our understanding of disease mechanisms beyond traditional immune pathways. In addition, we found distinct gut microbial profiles in Sjögren's disease participants, although ocular surface microbiome showed no significant differences. Such findings may suggest possible new therapeutic targets and allow for Sjögren's disease patient stratification. However, validation in larger cohorts is needed to establish clinical significance and potential applications in Sjögren's disease.

A Strong Dysregulated Myeloid Component in the Epigenetic Landscape of Systemic Sclerosis: An Integrated DNA Methylome and Transcriptome Analysis

OBJECTIVE

Nongenetic factors influence systemic sclerosis (SSc) pathogenesis, underscoring epigenetics as a relevant contributor to the disease. We aimed to unravel DNA methylation abnormalities associated with SSc through an epigenome-wide association study.

METHODS

We analyzed DNA methylation data from whole-blood samples in 179 patients with SSc and 241 unaffected individuals to identify differentially methylated positions (DMPs) with a false discovery rate (FDR) <0.05. These results were further integrated with RNA sequencing data from the same patients to assess their functional consequence. Additionally, we examined the impact of DNA methylation changes on transcription factors and analyzed the relationship between alterations of the methylation and gene expression profile and serum proteins levels.

RESULTS

This analysis yielded 525 DMPs enriched in immune-related pathways, with leukocyte cell-cell adhesion being the most significant (FDR = 4.91 × 10-9), prioritizing integrins as they were exposed by integrating methylome and transcriptome data. Furthermore, through this integrative approach, we observed an enrichment of neutrophil-related pathways, highlighting this myeloid cell type as a relevant contributor in SSc pathogenesis. In addition, we uncovered novel profibrotic and proinflammatory mechanisms involved in the disease. Finally, the altered epigenetic and transcriptomic signature revealed an increased activity of CCAAT/enhancer-binding protein transcription factor family in SSc, which is crucial in the myeloid lineage development.

CONCLUSION

Our findings uncover the impaired epigenetic regulation of the disease and its impact on gene expression, identifying new molecules for potential clinical applications and improving our understanding of SSc pathogenesis.

Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement

OBJECTIVE

This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).

METHODS

Totally, 91 participants were enrolled between February 2023 and January 2024 including 58 SLE patients [30 with nonrenal-SLE and 28 with Lupus nephritis (LN)] and 33 healthy controls (HC). Ultracentrifugation was used to isolate serum exosomes, which were analyzed for their metabolic profiles using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Endogenous metabolites were identified via public metabolite databases. Random Forest, Lasso regression and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithms were employed to screen key metabolites, and a prediction model was constructed for SLE diagnosis and LN discrimination. ROC curves were constructed to determine the potential of these differential exosome-derived metabolites for the diagnosis of SLE. Furthermore, Spearman's correlation was employed to evaluate the potential links between exosome-derived metabolites and the clinical parameters which reflect disease progression.

RESULTS

A total of 586 endogenous serum exosome-derived metabolites showed differential expression, with 225 exosome-derived metabolites significantly upregulated, 88 downregulated and 273 exhibiting no notable changes in the HC and SLE groups. Machine learning algorithms revealed three differential metabolites: Pro-Asn-Gln-Met-Ser, C24:1 sphingolipid, and protoporphyrin IX, which exhibited AUC values of 0.998, 0.992 and 0.969 respectively, for distinguishing between the SLE and HC groups, with a combined AUC of 1.0. In distinguishing between the LN and SLE groups, the AUC values for these metabolites were 0.920, 0.893 and 0.865, respectively, with a combined AUC of 0.931, demonstrating excellent diagnostic performance. Spearman correlation analysis revealed that Pro-Asn-Gln-Met-Ser and protoporphyrin IX were positively correlated with the SLE Disease Activity Index (SLEDAI) scores, urinary protein/creatinine ratio (ACR) and urinary protein levels, while C24:1 sphingolipid exhibited a negative correlation.

CONCLUSIONS

This study provides the first comprehensive characterization of the exosome-derived metabolites in SLE and established a promising prediction model for SLE and LN discrimination. The correlation between exosome-derived metabolites and key clinical parameters strongly indicated their potential role in SLE pathological progression.

Systemic lupus erythematosus: updated insights on the pathogenesis, diagnosis, prevention and therapeutics

Systemic lupus erythematosus (SLE) is a chronic inflammatory illness with heterogeneous clinical manifestations covering multiple organs. Diversified types of medications have been shown effective for alleviating SLE syndromes, ranging from cytokines, antibodies, hormones, molecular inhibitors or antagonists, to cell transfusion. Drugs developed for treating other diseases may benefit SLE patients, and agents established as SLE therapeutics may be SLE-inductive. Complexities regarding SLE therapeutics render it essential and urgent to identify the mechanisms-of-action and pivotal signaling axis driving SLE pathogenesis, and to establish innovative SLE-targeting approaches with desirable therapeutic outcome and safety. After introducing the research history of SLE and its epidemiology, we categorized primary determinants driving SLE pathogenesis by their mechanisms; combed through current knowledge on SLE diagnosis and grouped them by disease onset, activity and comorbidity; introduced the genetic, epigenetic, hormonal and environmental factors predisposing SLE; and comprehensively categorized preventive strategies and available SLE therapeutics according to their functioning mechanisms. In summary, we proposed three mechanisms with determinant roles on SLE initiation and progression, i.e., attenuating the immune system, restoring the cytokine microenvironment homeostasis, and rescuing the impaired debris clearance machinery; and provided updated insights on current understandings of SLE regarding its pathogenesis, diagnosis, prevention and therapeutics, which may open an innovative avenue in the fields of SLE management.

Identification of Epigenetic Alteration of the IFI44L Gene in B Cells of Sjogren's Syndrome as a Clinical Biomarker and Molecular Significance

Objective

Type 1 interferon (IFN-I)-related genes play a critical role in Sjögren's syndrome (SS). However, study on its role and impact in peripheral blood B cells of SS is limited. This study investigated gene expression and epigenetic changes in IFI44L, analyzing its correlation with disease activity and clinical indicators.

Methods

Differentially expressed genes (DEGs) were identified from the GSE199868 dataset, while IFN-I-related genes were collected from GeneCards. Intersection analysis revealed IFN-I-related DEGs in SS. ClueGO, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, PPI network construction, and hub gene identification were conducted, with hub genes validated in GSE135809. Following this, we recruited 30 SS patients as the disease group and 11 healthy individuals as the control group. Clinical information and peripheral blood samples were collected from all participants. After isolating B cells from the peripheral blood, we used quantitative real-time polymerase chain reaction (RT-qPCR) and pyrosequencing to examine the mRNA expression and DNA methylation status of the IFI44L gene. Further analyses were conducted in conjunction with clinical indicators.

Results

GSE199868 analysis revealed 125 upregulated and 16 downregulated DEGs. Among 2794 IFN-I-related genes from GeneCards, 26 DEGs overlapped, enriched in viral genome replication and IFN-I pathways. 14 hub genes were identified, with 7 genes confirmed in GSE135809: ISG15, IFIT1, OASL, IFI6, RSAD2, IFI44L, and USP18. IFI44L mRNA expression was significantly higher in SS B cells (P < 0.05), while its DNA methylation status was significantly lower (P < 0.05). IFI44L expression correlated positively with ESSDAI, ESSPRI, and IgG levels, while methylation correlated negatively with ESSDAI and ESSPRI (P < 0.05). ROC analysis revealed that the IFI44L gene had high diagnostic value (AUC = 0.8515).

Conclusion

The study highlights the clinical relevance of IFI44L mRNA expression and DNA hypomethylation in SS, underscoring its potential as a biomarker for disease activity and progression.

Energy metabolism in health and diseases

Energy metabolism is indispensable for sustaining physiological functions in living organisms and assumes a pivotal role across physiological and pathological conditions. This review provides an extensive overview of advancements in energy metabolism research, elucidating critical pathways such as glycolysis, oxidative phosphorylation, fatty acid metabolism, and amino acid metabolism, along with their intricate regulatory mechanisms. The homeostatic balance of these processes is crucial; however, in pathological states such as neurodegenerative diseases, autoimmune disorders, and cancer, extensive metabolic reprogramming occurs, resulting in impaired glucose metabolism and mitochondrial dysfunction, which accelerate disease progression. Recent investigations into key regulatory pathways, including mechanistic target of rapamycin, sirtuins, and adenosine monophosphate-activated protein kinase, have considerably deepened our understanding of metabolic dysregulation and opened new avenues for therapeutic innovation. Emerging technologies, such as fluorescent probes, nano-biomaterials, and metabolomic analyses, promise substantial improvements in diagnostic precision. This review critically examines recent advancements and ongoing challenges in metabolism research, emphasizing its potential for precision diagnostics and personalized therapeutic interventions. Future studies should prioritize unraveling the regulatory mechanisms of energy metabolism and the dynamics of intercellular energy interactions. Integrating cutting-edge gene-editing technologies and multi-omics approaches, the development of multi-target pharmaceuticals in synergy with existing therapies such as immunotherapy and dietary interventions could enhance therapeutic efficacy. Personalized metabolic analysis is indispensable for crafting tailored treatment protocols, ultimately providing more accurate medical solutions for patients. This review aims to deepen the understanding and improve the application of energy metabolism to drive innovative diagnostic and therapeutic strategies.

Epigenetic attenuation of interferon signaling drives aging-related improvements in systemic lupus

In the general human population, aging is associated with a rise in systemic inflammation, primarily involving innate immune pathways related to interferon (IFN), toll-like receptor, and cytokine signaling. In systemic lupus erythematosus (SLE), a prototypical systemic autoimmune disease, aging is distinctly associated with improvements in disease activity, suggesting a unique relationship between aging and inflammation in this disease. Using a multi-omic approach incorporating transcriptional profiling, single cell RNA sequencing, proteomics and methylation analysis, we studied age-related changes in the immune profiles of 287 SLE patients between 20 and 83 years old, and compared the results against 928 healthy controls aged between 21 and 89 years old. In contrast to the increase in inflammatory gene expression that occurs with aging in most healthy adults, SLE patients exhibited the opposite. Most notable was a decrease in type I IFN signaling that was evident across multiple cell types, with CD56-dim natural killer (NK) cells, CD4 + effector memory T cells, and naïve B cells exhibiting the most significant differences. We found that aging in SLE patients was also associated with decreased IFN-α2 and IFN-λ1 levels, and differential methylation of the genome. Notably, of the genes both downregulated and hypermethylated with older age, IFN-related genes were disproportionately represented, suggesting that age-related decreases in IFN signaling were driven in part by epigenetic silencing. Both SLE patients and healthy controls demonstrated age-related declines in naïve T cells and lymphoid progenitor cells, but only SLE patients demonstrated age-related increases in CD56-dim NK cells. Taken together, our work provides new insight into the phenomenon of inflammaging and the unique clinical improvement in disease activity that occurs in SLE patients as they age.

An updated review on abnormal epigenetic modifications in the pathogenesis of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. The inconsistent prevalence of SLE between monozygotic twins suggests that environmental factors affect the occurrence of this disease. Abnormal epigenetic regulation is strongly associated with the pathogenesis of SLE. Epigenetic mechanisms may be involved in the development of lupus through DNA methylation, histone modification, noncoding RNAs, and other modifications. This review aims to show numerous studies as a treasure map to better understand the effects of aberrant epigenetic modification in the onset and development of SLE, which will benefit the current basic research and provide potential diagnostic biomarkers or therapeutic targets for SLE.

Identification of IFITM3 as a diagnostic biomarker of systemic lupus erythematosus and its association with disease activity based on multi-omics and experimental verification

BACKGROUND

Systemic lupus erythematosus is a clinically heterogeneous autoimmune disease that lacks reliable diagnostic biomarkers. In our study, we aimed to identify a novel biomarker for the diagnosis and disease activity monitoring of SLE.

METHODS

Bulk RNA and scRNA-seq datasets were obtained from the Gene Expression Omnibus database. In this study, differential analysis, cell-cell communication algorithm, functional enrichment analysis, human protein map database analysis, protein-protein interaction analysis and immune cell infiltration analysis were utilized to identify the hub genes between SLE and healthy groups. Furthermore, clinical data from 68 SLE patients and 31 healthy controls were collected for verification. Changes in IFITM3 levels were confirmed through quantitative real-time polymerase chain reaction, western blotting, and flow cytometry analyses.

RESULT

Bioinformatic analyses showed that IFITM3 expression was significantly upregulated in peripheral monocytes from patients with SLE. IFITM3 mRNA levels showed a significant diagnostic value for SLE, with an AUC value of 87.14%. IFITM3 expression was associated with the systemic lupus erythematosus disease activity index, as well as C3, C4, and IgG levels. The results of Chi-square test showed that those in the IFITM3-positive group had a higher percentage of several clinical manifestations such as thrombocytopenia, leukopenia, low complement, and fever.

CONCLUSIONS

These findings indicated an obviously increased expression of IFITM3 in peripheral blood monocytes of patients with SLE and verified IFITM3 as a promising diagnostic marker for SLE and associated with disease activity.

Changes in DNA methylation are associated with systemic lupus erythematosus flare remission and clinical subtypes

BACKGROUND

Systemic lupus erythematosus (SLE) has numerous symptoms across organs and an unpredictable flare-remittance pattern. This has made it challenging to understand drivers of long-term SLE outcomes. Our objective was to identify whether changes in DNA methylation over time, in an actively flaring SLE cohort, were associated with remission and whether these changes meaningfully subtype SLE patients.

METHODS

Fifty-nine multi-ethnic SLE patients had clinical visits and DNA methylation profiles at a flare and approximately 3 months later. Methylation was measured using the Illumina EPIC array. We identified sites where methylation change between visits was associated with remission at the follow-up visit using limma package and a time x remission interaction term. Models adjusted for batch, age at diagnosis, time between visits, age at flare, sex, medications, and cell-type proportions. Separately, a paired T-test identified Bonferroni significant methylation sites with ≥ 3% change between visits (n = 546). Methylation changes at these sites were used for unsupervised consensus hierarchical clustering. Associations between clusters and patient features were assessed.

RESULTS

Nineteen patients fully remitted at the follow-up visit. For 1,953 CpG sites, methylation changed differently for remitters vs. non-remitters (Bonferroni p < 0.05). Nearly half were within genes regulated by interferon. The largest effect was at cg22873177; on average, remitters had 23% decreased methylation between visits while non-remitters had no change. Three SLE patient clusters were identified using methylation differences agnostic of clinical outcomes. All Cluster 1 subjects (n = 12) experienced complete flare remission, despite similar baseline disease activity scores, medications, and demographics as other clusters. Methylation changes at six CpG sites, including within immune-related CD45 and IFI genes, were particularly distinct for each cluster, suggesting these may be good candidates for stratifying patients in the future.

CONCLUSIONS

Changes in DNA methylation during active SLE were associated with remission status and identified subgroups of SLE patients with several distinct clinical and biological characteristics. DNA methylation patterns might help inform SLE subtypes, leading to targeted therapies based on relevant underlying biological pathways.

Autoimmune disease: a view of epigenetics and therapeutic targeting

Autoimmune diseases comprise a large group of conditions characterized by a complex pathogenesis and significant heterogeneity in their clinical manifestations. Advances in sequencing technology have revealed that in addition to genetic susceptibility, various epigenetic mechanisms including DNA methylation and histone modification play critical roles in disease development. The emerging field of epigenetics has provided new perspectives on the pathogenesis and development of autoimmune diseases. Aberrant epigenetic modifications can be used as biomarkers for disease diagnosis and prognosis. Exploration of human epigenetic profiles revealed that patients with autoimmune diseases exhibit markedly altered DNA methylation profiles compared with healthy individuals. Targeted cutting-edge epigenetic therapies are emerging. For example, DNA methylation inhibitors can rectify methylation dysregulation and relieve patients. Histone deacetylase inhibitors such as vorinostat can affect chromatin accessibility and further regulate gene expression, and have been used in treating hematological malignancies. Epigenetic therapies have opened new avenues for the precise treatment of autoimmune diseases and offer new opportunities for improved therapeutic outcomes. Our review can aid in comprehensively elucidation of the mechanisms of autoimmune diseases and development of new targeted therapies that ultimately benefit patients with these conditions.

The dual effects of Benzo(a)pyrene/Benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide on DNA Methylation

Benzo(a)pyrene (BaP) is one of the most thoroughly studied polycyclic aromatic hydrocarbons(PAHs) and a widespread organic pollutant in various areas of human life. Its teratogenic, immunotoxic and carcinogenic effects on organisms are well documented and widely recognized by researchers. In the body, BaP is enzymatically converted to form a more active benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE). BaP/BPDE has the potential to trigger gene mutations, influence epigenetic modifications and cause damage to cellular structures, ultimately contributing to disease onset and progression. However, there are different points of view when studying epigenetics using BaP/BPDE. On the one hand, it is claimed in cancer research that BaP/BPDE contributes to gene hypermethylation and, in particular, induces the hypermethylation of tumor's suppressor gene promoters, leading to gene silencing and subsequent cancer development. Conversely, studies in human and animal populations suggest that exposure to BaP results in genome-wide DNA hypomethylation, potentially leading to adverse outcomes in inflammatory diseases. This apparent contradiction has not been summarized in research for almost four decades. This article presents a comprehensive review of the current literature on the influence of BaP/BPDE on DNA methylation regulation. It demonstrates that BaP/BPDE exerts a dual-phase regulatory effect on methylation, which is influenced by factors such as the concentration and duration of BaP/BPDE exposure, experimental models and detection methods used in various studies. Acute/high concentration exposure to BaP/BPDE often results in global demethylation of DNA, which is associated with inhibition of DNA methyltransferase 1 (DNMT1) after exposure. At certain specific gene loci (e.g., RAR-β), BPDE can form DNA adducts, recruiting DNMT3 and leading to hypermethylation at specific sites. By integrating these different mechanisms, our goal is to unravel the patterns and regulations of BaP/BPDE-induced DNA methylation changes and provide insights into future precision therapies targeting epigenetics.

5-Hydroxymethylcytosine in circulating cell-free DNA as a potential diagnostic biomarker for SLE

BACKGROUND

SLE is a complex autoimmune disease with heterogeneous manifestations and unpredictable outcomes. Early diagnosis is challenging due to non-specific symptoms, and current treatments only manage symptoms. Epigenetic alternations, including 5-Hydroxymethylome (5hmC) modifications, are important contributors to SLE pathogenesis. However, the 5hmC modification status in circulating cell-free DNA (cfDNA) of patients with SLE remains largely unexplored. We investigated the distribution of 5hmC in cfDNA of patients with SLE and healthy controls (HCs), and explored its potential as an SLE diagnosis marker.

METHODS

We used 5hmC-Seal to generate genome-wide 5hmC profiles of plasma cfDNA and bioinformatics analysis to screen differentially hydroxymethylated regions (DhMRs). In vitro mechanistic exploration was conducted to investigate the regulatory effect of CCCTC-binding factor (CTCF) in 5hmC candidate biomarkers.

RESULTS

We found distinct differences in genomic regions and 5hmC modification motif patterns between patients with SLE and HCs, varying with disease progression. Increased 5hmC modification enrichment was detected in SLE. Additionally, we screened 151 genes with hyper-5hmC, which are significantly involved in SLE-related processes, and 5hmC-modified BCL2, CD83, ETS1 and GZMB as SLE biomarkers. Our findings suggest that CTCF regulates 5hmC modification of these genes by recruiting TET (ten-eleven translocation) protein, and CTCF knockdown affected the protein expression of these genes in vitro.

CONCLUSIONS

Our findings demonstrate the increased 5hmC distribution in plasma cfDNA in different disease activity in patients with SLE compared with HCs and relating DhMRs involved in SLE-associated pathways. Furthermore, we identified a panel of SLE relevant biomarkers, and these viewpoints could provide insight into the pathogenesis of SLE.

Identification of NET formation and the renoprotective effect of degraded NETs in lupus nephritis

To explore molecular biomarkers associated with the pathophysiology and therapy of lupus nephritis (LN), we conducted a joint analysis of transcriptomic data from 40 peripheral blood mononuclear cells (PBMCs) (GSE81622) and 21 kidney samples (GSE112943) from the Gene Expression Omnibus database using bioinformatics. A total of 976 and 2,427 differentially expressed genes (DEGs) were identified in PBMCs and renal tissues. Seven and two functional modules closely related to LN were identified. Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney. Subsequently, 16 core genes closely associated with LN were verified by protein-protein interaction screening and quantitative PCR. In vitro cell models and MRL/lpr mouse models confirmed that the abnormal expression of these core genes was closely linked to neutrophil extracellular traps (NETs) generated by neutrophil activation, while degradation of NETs led to downregulation of core gene expression, thereby improving pathological symptoms of LN. Therefore, identification of patients with systemic lupus erythematosus exhibiting abnormal expression patterns for these core genes may serve as a useful indicator for kidney involvement. In addition, targeting neutrophils to modulate their activation levels and inhibit aberrant expression of these genes represents a potential therapeutic strategy for treating LN. NEW & NOTEWORTHY The mechanisms by which immune cells cause kidney injury in lupus nephritis are poorly understood. We integrated and analyzed the transcriptomic features of PBMCs and renal tissues from the GEO database to identify key molecular markers associated with neutrophil activation. We confirmed that neutrophil extracellular traps (NETs) formed by neutrophil activation promoted the upregulation of key genes in cell and animal models. Targeted degradation of NETs significantly ameliorated kidney injury in MRL/lpr mice.

Environment and systemic autoimmune rheumatic diseases: an overview and future directions

Introduction

Despite progress in our understanding of disease pathogenesis for systemic autoimmune rheumatic diseases (SARD), these diseases are still associated with high morbidity, disability, and mortality. Much of the strongest evidence to date implicating environmental factors in the development of autoimmunity has been based on well-established, large, longitudinal prospective cohort studies.

Methods

Herein, we review the current state of knowledge on known environmental factors associated with the development of SARD and potential areas for future research.

Results

The risk attributable to any particular environmental factor ranges from 10-200%, but exposures are likely synergistic in altering the immune system in a complex interplay of epigenetics, hormonal factors, and the microbiome leading to systemic inflammation and eventual organ damage. To reduce or forestall the progression of autoimmunity, a better understanding of disease pathogenesis is still needed.

Conclusion

Owing to the complexity and multifactorial nature of autoimmune disease, machine learning, a type of artificial intelligence, is increasingly utilized as an approach to analyzing large datasets. Future studies that identify patients who are at high risk of developing autoimmune diseases for prevention trials are needed.

Recognition of differently expressed genes and DNA methylation markers in patients with Lupus nephritis

Background and Objectives

Systemic lupus erythematosus (SLE) is distinguished by dysregulated immune system activity, resulting in a spectrum of clinical manifestations, with lupus nephritis being particularly prominent. This study endeavors to discern novel targets as potential therapeutic markers for this condition.

Methods

Weighted correlation network analysis (WGCNA) was used to construct the network and select the key hub genes in the co-expression module based on the gene expression dataset GSE81622. Subsequently, functional enrichment and pathway analysis were performed for SLE and lupus nephritis. In addition, also identify genes and differences in SLE with lupus nephritis and methylation site. Finally, qRT-PCR and western blot were used to verify the up-regulated expression levels of the selected key genes.

Results

Within the co-expression modules constructed by WGCNA, the MElightcyan module exhibited the strongest positive correlation with lupus nephritis (0.4, P = 0.003), while showing a weaker correlation with the control group SLE (0.058) and a negative correlation with the control group (-0.41, P = 0.002). Additionally, the MEgreenyellow module displayed the highest positive correlation with SLE (0.25), but its P value was 0.06, which did not reach statistical significance(P > 0.05). Furthermore, it had a negative correlation with the control group was (-0.38, P = 0.004). The module associated with lupus nephritis was characterized by processes such as neutrophil activation (neutrophil_activation), neutrophil degranulation (neutrophil_degranulation), neutrophil activation involved in immune response (neutrophil_activation_involved_in_immune_response), neutrophils mediated immune (neutrophil_mediated_immunity) and white blood cells degranulation (leukocyte_degranulation) and so on the adjustment of the process. Secondly, in the analysis of SLE samples, the identification of differentially expressed genes revealed 125 genes, with 49 being up-regulated and 76 down-regulated. In the case of lupus nephritis samples, 156 differentially expressed genes were discerned, include in 70 up-regulated and 86 down-regulated genes. When examining differential methylation sites, we observed 12432 such sites in the SLE sample analysis, encompassing 2260 hypermethylation sites and 10172 hypomethylation sites. In the lupus nephritis samples analysis, 9613 differential methylation sites were identified, comprising 4542 hypermethylation sites and 5071 hypomethylation sites. Substantiating our findings, experimental validation of the up-regulated genes in lupus nephritis confirmed increased levels of gene expression and protein expression for CEACAM1 and SLC2A5.

Conclusions

We have identified several genes, notably CEACAM1 and SLC2A5, as potential markers for lupus nephritis. Their elevated expression levels and reduced DNA methylation in lupus nephritis contribute to a more comprehensive understanding of the aberrant epigenetic regulation of expression in this condition. These findings hold significant implications for the diagnosis and therapeutic strategies of lupus nephritis.

A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes

In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.

DNA methylation of IFI44L as a potential blood biomarker for childhood-onset systemic lupus erythematosus

BACKGROUND

IFN-induced protein 44-like (IFI44L) promoter methylation has been demonstrated to serve as an effective blood diagnostic biomarker for adult-onset SLE. However, its utility as a diagnostic marker for childhood-onset SLE (cSLE) remains to be verified.

METHODS

Initially, we conducted a differential analysis of gene methylation and mRNA expression patterns in cSLE whole blood samples obtained from the public GEO database to determine IFI44L gene expression and assess the methylation status at its CpG sites. Subsequently, we collected clinical whole blood samples from 49 cSLE patients and 12 healthy children, employing an HRM-qPCR-based IFI44L methylation detection technique to evaluate its diagnostic efficacy in pediatric clinical practice.

RESULTS

A total of 26 hypomethylated, highly expressed genes in cSLE were identified by intersecting differentially expressed genes (DEGs) and differentially methylation genes (DMGs). GO enrichment analysis for these 26 genes indicated a robust association with type I IFN. Among the overlapping genes, IFI44L exhibited the most pronounced differential expression and methylation. In subsequent clinical validation experiments, IFI44L methylation was confirmed as an effective blood-based diagnostic biomarker for cSLE, achieving an AUC of 0.867, a sensitivity of 0.753, and a specificity of 1.000.

CONCLUSIONS

IFI44L methylation is a promising blood biomarker for cSLE.

IMPACT

IFI44L promoter methylation was reported to serve as a highly sensitive and specific diagnostic marker for adult-onset SLE. However, the diagnostic efficacy of IFI44L in childhood-onset SLE (cSLE) still remains to be confirmed. In this study, we utilized bioinformatics analysis and conducted clinical experiments to demonstrate that IFI44L methylation can also serve as a promising blood biomarker for cSLE. The findings of this study can facilitate the diagnosis of cSLE and broaden our understanding of its molecular mechanisms, with a particular focus on those related to type I interferons.

DNA methylation in human diseases

Aberrant epigenetic modifications, particularly DNA methylation, play a critical role in the pathogenesis and progression of human diseases. The current review aims to reveal the role of aberrant DNA methylation in the pathogenesis and progression of diseases and to discuss the original data obtained from international research laboratories on this topic. In the review, we mainly summarize the studies exploring the role of aberrant DNA methylation as diagnostic and prognostic biomarkers in a broad range of human diseases, including monogenic epigenetics, autoimmunity, metabolic disorders, hematologic neoplasms, and solid tumors. The last section provides a general overview of the possibility of the DNA methylation machinery from the perspective of pharmaceutic approaches. In conclusion, the study of DNA methylation machinery is a phenomenal intersection that each of its ways can reveal the mysteries of various diseases, introduce new diagnostic and prognostic biomarkers, and propose a new patient-tailored therapeutic approach for diseases.

Disease activity drives divergent epigenetic and transcriptomic reprogramming of monocyte subpopulations in systemic lupus erythematosus

OBJECTIVES

Systemic lupus erythematosus (SLE) is characterised by systemic inflammation involving various immune cell types. Monocytes, pivotal in promoting and regulating inflammation in SLE, differentiate from classic monocytes into intermediate and non-classic monocytes, assuming diverse roles and changing their proportions in inflammation. In this study, we investigated the epigenetic and transcriptomic profiles of these and novel monocyte subsets in SLE in relation to activity and progression.

METHODS

We obtained the DNA methylomes and transcriptomes of classic, intermediate, non-classic monocytes in patients with SLE (at first and follow-up visits) and healthy donors. We integrated these data with single-cell transcriptomics of SLE and healthy donors and interrogated their relationships with activity and progression.

RESULTS

In addition to shared DNA methylation and transcriptomic alterations associated with a strong interferon signature, we identified monocyte subset-specific alterations, especially in DNA methylation, which reflect an impact of SLE on monocyte differentiation. SLE classic monocytes exhibited a proinflammatory profile and were primed for macrophage differentiation. SLE non-classic monocytes displayed a T cell differentiation-related phenotype, with Th17-regulating features. Changes in monocyte proportions, DNA methylation and expression occurred in relation to disease activity and involved the STAT pathway. Integration of bulk with single-cell RNA sequencing datasets revealed disease activity-dependent expansion of SLE-specific monocyte subsets, further supported the interferon signature for classic monocytes, and associated intermediate and non-classic populations with exacerbated complement activation.

CONCLUSIONS

Disease activity in SLE drives a subversion of the epigenome and transcriptome programme in monocyte differentiation, impacting the function of different subsets and allowing to generate predictive methods for activity and progression.

Significant heightened methylation levels of RUNX3 gene promoter in patients with systemic lupus erythematosus

OBJECTIVE

Researchers are actively investigating new diagnostic and prognostic biomarkers that offer improved sensitivity and specificity for systemic lupus erythematosus (SLE). One area of interest is DNA methylation changes. Previous studies have shown a connection between the RUNX3 gene dysfunction and SLE. In this study, the focus was on examining the methylation level of the RUNX3 promoter in peripheral blood mononuclear cells (PBMCs) of SLE patients and healthy individuals.

METHODS

A total of 80 individuals diagnosed with SLE from Iran, along with 77 healthy individuals, were included. The methylation levels of the RUNX3 gene in the extracted DNA were evaluated using the MethyQESD method. To determine the diagnostic effectiveness of the RUNX3 promoter methylation level, a receiver operating characteristic (ROC) curve was generated.

RESULTS

The methylation of the RUNX3 promoter was found to be significantly higher in patients with SLE compared to healthy individuals (p < .001). This difference in methylation levels was observed between SLE patients and healthy individuals and between SLE patients with renal involvement and those without renal involvement (86.29 ± 10.30 vs 40.28 ± 24.21, p < .001). ROC analyses revealed that the methylation level of the RUNX3 promoter had a diagnostic power of 0.769 [95% CI (0.681-0.814)] for SLE. Additionally, there was a positive correlation between the RUNX3 methylation level and levels of creatinine and C4.

CONCLUSION

The findings of this study emphasize the potential use of RUNX3 methylation levels in PBMCs of SLE patients as biomarkers for diagnosing the disease, predicting renal damage, and assessing disease activity.

Methylation in cornea and corneal diseases: a systematic review

Corneal diseases are among the primary causes of blindness and vision loss worldwide. However, the pathogenesis of corneal diseases remains elusive, and diagnostic and therapeutic tools are limited. Thus, identifying new targets for the diagnosis and treatment of corneal diseases has gained great interest. Methylation, a type of epigenetic modification, modulates various cellular processes at both nucleic acid and protein levels. Growing evidence shows that methylation is a key regulator in the pathogenesis of corneal diseases, including inflammation, fibrosis, and neovascularization, making it an attractive potential therapeutic target. In this review, we discuss the major alterations of methylation and demethylation at the DNA, RNA, and protein levels in corneal diseases and how these dynamics contribute to the pathogenesis of corneal diseases. Also, we provide insights into identifying potential biomarkers of methylation that may improve the diagnosis and treatment of corneal diseases.

MicroRNA-98-5p Inhibits IFI44L-Mediated Differentiation of Dendritic Cells and Activation of Interferon Pathway in Systemic Lupus Erythematosus

MicroRNA-98-5p (miR-98-5p) plays a protective role in the pathogenesis of autoimmune diseases through anti-inflammatory effects, but little is known about its role in Systemic lupus erythematosus (SLE). Our previous study suggested Interferon-inducible 44 like (IFI44L) overexpressed in monocytes which contributes to the pathogenesis of SLE by enhancing the maturation and functions of monocyte-derived dendritic cells (Mo-DCs), and miR-98-5p can regulate the expression of IFI44L. In this study, we identified miR-98-5p lowly expressed in both peripheral blood mononuclear cells (PBMCs) and monocytes of SLE patients along with high expression of IFI44L. IFI44L serves as target gene of miR-98-5p which inhibits differentiation of Mo-DCs and IFI44L-mediated activation of interferon pathway. We further showed that miR-98-5p promotes methylation of the IFI44L promoter to down-regulate its expression in SLE. Our results reveal an important role for miR-98-5p in the IFI44L-mediated immune imbalance of SLE and suggest a potential therapeutic target for SLE in the future.

Aberrant H3K4me3 modification of immune response genes in CD4+ T cells of patients with systemic lupus erythematosus

BACKGROUND

Increasing evidence has highlighted the significant role of histone modifications in pathogenesis of systemic lupus erythematosus (SLE). However, few studies have comprehensively analyzed trimethylation of histone H3 lysine 4 (H3K4me3) features at specific immune gene loci in SLE patients.

METHODS

We conducted H3K4me3 chromatin immunoprecipitation sequencing (ChIP-seq) on CD4+ T cells from SLE patients and healthy controls (HC). Differential H3K4me3 peaks were identified, followed by enrichment analysis. We integrated online RNA-seq and DNA methylation datasets to explore the relationship between H3K4me3 modification, DNA methylation and gene expression. We validated several upregulated peak regions by ChIP-qPCR and confirmed their impact on gene expression using RT-qPCR. Finally, we investigated the impact of H3K4 methyltransferases KMT2A on the expression of immune response genes.

RESULTS

we identified 147 downregulated and 2701 upregulated H3K4me3 peaks in CD4+ T cells of SLE. The upregulated peaks primarily classified as gained peaks and enriched in immune response genes such as FCGR2A, C5AR1, SERPING1 and OASL. Genes with upregulated H3K4me3 and downregulated DNA methylations in the promoter were highly expressed in SLE patients. These genes, including OAS1, IFI27 and IFI44L, were enriched in immune response pathways. The IFI44L locus also showed increased H3K27ac modification, chromatin accessibility and chromatin interactions in SLE. Moreover, knockdown of KMT2A can downregulate the expression of immune response genes in T cells.

CONCLUSION

Our study uncovers dysregulated H3K4me3 modification patterns in immune response genes loci, which also exhibit downregulated DNA methylation and higher mRNA expression in CD4+ T cells of SLE patients.

Functional significance of DNA methylation: epigenetic insights into Sjögren's syndrome

Sjögren's syndrome (SjS) is a systemic, highly diverse, and chronic autoimmune disease with a significant global prevalence. It is a complex condition that requires careful management and monitoring. Recent research indicates that epigenetic mechanisms contribute to the pathophysiology of SjS by modulating gene expression and genome stability. DNA methylation, a form of epigenetic modification, is the fundamental mechanism that modifies the expression of various genes by modifying the transcriptional availability of regulatory regions within the genome. In general, adding a methyl group to DNA is linked with the inhibition of genes because it changes the chromatin structure. DNA methylation changes the fate of multiple immune cells, such as it leads to the transition of naïve lymphocytes to effector lymphocytes. A lack of central epigenetic enzymes frequently results in abnormal immune activation. Alterations in epigenetic modifications within immune cells or salivary gland epithelial cells are frequently detected during the pathogenesis of SjS, representing a robust association with autoimmune responses. The analysis of genome methylation is a beneficial tool for establishing connections between epigenetic changes within different cell types and their association with SjS. In various studies related to SjS, most differentially methylated regions are in the human leukocyte antigen (HLA) locus. Notably, the demethylation of various sites in the genome is often observed in SjS patients. The most strongly linked differentially methylated regions in SjS patients are found within genes regulated by type I interferon. This demethylation process is partly related to B-cell infiltration and disease progression. In addition, DNA demethylation of the runt-related transcription factor (RUNX1) gene, lymphotoxin-α (LTA), and myxovirus resistance protein A (MxA) is associated with SjS. It may assist the early diagnosis of SjS by serving as a potential biomarker. Therefore, this review offers a detailed insight into the function of DNA methylation in SjS and helps researchers to identify potential biomarkers in diagnosis, prognosis, and therapeutic targets.

Identification of m6A-Related Biomarkers in Systemic Lupus Erythematosus: A Bioinformation-Based Analysis

Background

Systemic Lupus Erythematosus (SLE), a prototypical autoimmune disorder, presents a challenge due to the absence of reliable biomarkers for discerning organ-specific damage within SLE. A growing body of evidence underscores the pivotal involvement of N6-methyladenosine (m6A) in the etiology of autoimmune conditions.

Methods

The datasets, which primarily encompassed the expression profiles of m6A regulatory genes, were retrieved from the Gene Expression Omnibus (GEO) repository. The optimal model, selected from either Random Forest (RF) or Support Vector Machine (SVM), was employed for the development of a predictive nomogram model. To identify pivotal genes associated with SLE, a comprehensive screening process was conducted utilizing LASSO, SVM-RFE, and RF techniques. Within the realm of SLE susceptibility, Weighted Gene Co-expression Network Analysis (WGCNA) was harnessed to delineate relevant modules and hub genes. Additionally, MeRIP-qPCR assays were performed to elucidate key genes correlated with m6A targets. Furthermore, a Mendelian randomization study was conducted based on genome-wide association studies to assess the causative influence of MMP9 on ischemic stroke (IS), which is not only a severe cerebrovascular event but also a common complication of SLE.

Results

Twelve m6A regulatory genes was identified, demonstrating statistical significance (p < 0.05) and utilized for constructing a nomogram model using the RF algorithm. EPSTI1, USP18, HP, and MMP9, as the hub genes, were identified. MMP9 uniquely correlates with m6A modification and was causally linked to an increased risk of IS, as indicated by our inverse variance weighting analysis showing an odds ratio of 1.0134 (95% CI=1.0004-1.0266, p = 0.0440).

Conclusion

Our study identified twelve m6A regulators, shedding light on the molecular mechanisms underlying SLE risk genes. Importantly, our analysis established a causal relationship between MMP9, a key m6A-related gene, and ischemic stroke, a common complication of SLE, thereby providing critical insights for presymptomatic diagnostic approaches.

Serum Metabolic Fingerprints Characterize Systemic Lupus Erythematosus

Metabolic fingerprints in serum characterize diverse diseases for diagnostics and biomarker discovery. The identification of systemic lupus erythematosus (SLE) by serum metabolic fingerprints (SMFs) will facilitate precision medicine in SLE in an early and designed manner. Here, a discovery cohort of 731 individuals including 357 SLE patients and 374 healthy controls (HCs), and a validation cohort of 184 individuals (SLE/HC, 91/93) are constructed. Each SMF is directly recorded by nano-assisted laser desorption/ionization mass spectrometry (LDI MS) within 1 minute using 1 µL of native serum, which contains 908 mass to charge features. Sparse learning of SMFs achieves the SLE identification with sensitivity/specificity and area-under-the-curve (AUC) up to 86.0%/92.0% and 0.950 for the discovery cohort. For the independent validation cohort, it exhibits no performance loss by affording the sensitivity/specificity and AUC of 89.0%/100.0% and 0.992. Notably, a metabolic biomarker panel is screened out from the SMFs, demonstrating the unique metabolic pattern of SLE patients different from both HCs and rheumatoid arthritis patients. In conclusion, SMFs characterize SLE by revealing its unique metabolic pattern. Different regulation of small molecule metabolites contributes to the precise diagnosis of autoimmune disease and further exploration of the pathogenic mechanisms.

Identification of driver genes in lupus nephritis based on comprehensive bioinformatics and machine learning

Background

Lupus nephritis (LN) is a common and severe glomerulonephritis that often occurs as an organ manifestation of systemic lupus erythematosus (SLE). However, the complex pathological mechanisms associated with LN have hindered the progress of targeted therapies.

Methods

We analyzed glomerular tissues from 133 patients with LN and 51 normal controls using data obtained from the GEO database. Differentially expressed genes (DEGs) were identified and subjected to enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was utilized to identify key gene modules. The least absolute shrinkage and selection operator (LASSO) and random forest were used to identify hub genes. We also analyzed immune cell infiltration using CIBERSORT. Additionally, we investigated the relationships between hub genes and clinicopathological features, as well as examined the distribution and expression of hub genes in the kidney.

Results

A total of 270 DEGs were identified in LN. Using weighted gene co-expression network analysis (WGCNA), we clustered these DEGs into 14 modules. Among them, the turquoise module displayed a significant correlation with LN (cor=0.88, p<0.0001). Machine learning techniques identified four hub genes, namely CD53 (AUC=0.995), TGFBI (AUC=0.997), MS4A6A (AUC=0.994), and HERC6 (AUC=0.999), which are involved in inflammation response and immune activation. CIBERSORT analysis suggested that these hub genes may contribute to immune cell infiltration. Furthermore, these hub genes exhibited strong correlations with the classification, renal function, and proteinuria of LN. Interestingly, the highest hub gene expression score was observed in macrophages.

Conclusion

CD53, TGFBI, MS4A6A, and HERC6 have emerged as promising candidate driver genes for LN. These hub genes hold the potential to offer valuable insights into the molecular diagnosis and treatment of LN.

Demethylation of CDKN2A in systemic lupus erythematosus and rheumatoid arthritis: a blood biomarker for diagnosis and assessment of disease activity

INTRODUCTION/OBJECTIVES

Considering the phenotypic and serological heterogeneity of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA), significant challenges may intervene with the precise diagnosis. In this regard, numerous studies have shown that changes in DNA methylation levels can be used to distinguish between healthy individuals and those with SLE and RA, as well as to predict disease activity and prognosis.

METHODS

In the current study, we evaluated quantitative methylation level of CDKN2A promoter in peripheral blood mononuclear cells (PBMCs) of SLE and RA patients, and healthy controls by methylation-quantification of endonuclease-resistant DNA (MethyQESD), a bisulfite conversion-independent method.

RESULTS

Our findings revealed an excessive hypomethylation of CDKN2A in SLE and RA patients compared to healthy individuals (P < 0.001). Besides, by determining efficient cutoff value, the specificity of CDKN2A for correct diagnosis of healthy subjects was measured to be 77.30% and the sensitivity for SLE and RA diagnosis were 81.33%, and 72%, respectively. Furthermore, CDKN2A methylation level was shown to be positively associated with C3 and C4 levels and negatively associated with anti‑dsDNA concentration (P < 0.001). Moreover, a statistically significant difference in the DNA methylation levels of CDKN2A promoter was identified between SLE cases with age of ≤ 18 and patients with > 18 years of age (P = 0.025).

CONCLUSION

Our findings demonstrated that CDKN2A methylation levels in PBMCs of SLE and RA patients could be used as a promising diagnostic biomarker. The significant association between hypomethylation of CDKN2A promoter and disease activity factors in SLE patients, is suggesting that CDKN2A hypomethylation could be used as an alternative biomarker for assessment of disease activity. Key Points • Several studies have reported increased expression of CDKN2A in SLE and RA suggesting that it may be involved in the pathogenesis of these disorders. • CDKN2A hypomethylation has been implicated in different autoimmune diseases. • Our findings demonstrated that CDKN2A methylation levels in PBMCs of SLE and RA patients could be used as a promising diagnostic and prognostic biomarker.

Differences of RUNX2 gene promoter methylation and transcription level in ankylosing spondylitis

BACKGROUND AND OBJECTIVE

Ankylosing spondylitis is a refractory immune disease that seriously affects the life and work of patients. Epigenetic modifications, especially DNA methylation, have become a research hotspot in complex diseases. We aim to explore the changes in runt-related transcription factor 2 (RUNX2) gene promoter methylation and transcription level in AS.

METHOD

We detected the RUNX2 gene promoter methylation in 83 AS patients and 83 healthy controls (HCs), then inspected the mRNA difference of RUNX2 between 30 AS patients and 30 HCs by the quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR).

RESULTS

The RUNX2 gene promoter was hypomethylated in AS patients compared to HCs (p < .001). The research involved 4 CpG regions and 74 CpG sites of RUNX2, of which CpG-2, CpG-4 regions, and 18 CpG sites have been differentially methylated. The CpG-4 island methylation was negatively correlated with C-reactive protein (p < .05) in AS patients. In the qRT-PCR validation phase, the mRNA level of RUNX2 in AS patients was significantly higher than HCs (p < .05), and in AS patients who were treated with biologics, the methylation level of CpG-2 island showed a negative correlation to mRNA (p < .05). ROC results indicated that RUNX2 methylation and its transcription level have good potential to distinguish AS patients from HCs.

CONCLUSION

The RUNX2 gene promoter was hypomethylated in AS patients. Meanwhile, the qRT-PCR verified the up-regulated expression on the transcription level, suggesting the abnormal methylation of RUNX2 contributes to the pathogenesis of AS.

Whole-genome bisulfite sequencing identified the key role of the Src family tyrosine kinases and related genes in systemic lupus erythematosus

BACKGROUND

As a multisystemic autoimmune illness, the basic mechanisms behind the pathophysiology of systemic lupus erythematosus (SLE) remain poorly understood.

OBJECTIVE

We aimed to investigate the possible significance of SLE's DNA methylation and gain further insight into potential SLE-related biomarkers and therapeutic targets.

METHODS

We used whole genome bisulfite sequencing (WGBS) method to analyze DNA methylation in 4 SLE patients and 4 healthy people.

RESULTS

702 differentially methylated regions (DMRs) were identified, and 480 DMR-associated genes were annotated. We found the majority of the DMR-associated elements were enriched in repeat and gene bodies. The top 10 hub genes identified were LCK, FYB, PTK2B, LYN, CTNNB1, MAPK1, GNAQ, PRKCA, ABL1, and CD247. Compared to the control group, LCK and PTK2B had considerably decreased levels of mRNA expression in the SLE group. Receiver operating characteristic (ROC) curve suggested that LCK and PTK2B may be potential candidate biomarkers to predict SLE.

CONCLUSIONS

Our study improved comprehension of the DNA methylation patterns of SLE and identified potential biomarkers and therapeutic targets for SLE.

Type I Interferon Pathway-Related Hub Genes as a Potential Therapeutic Target for SARS-CoV-2 Omicron Variant-Induced Symptoms

BACKGROUND

The global pandemic of COVID-19 is caused by the rapidly evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical presentation of SARS-CoV-2 Omicron variant infection varies from asymptomatic to severe disease with diverse symptoms. However, the underlying mechanisms responsible for these symptoms remain incompletely understood.

METHODS

Transcriptome datasets from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients infected with the Omicron variant and healthy volunteers were obtained from public databases. A comprehensive bioinformatics analysis was performed to identify hub genes associated with the Omicron variant. Hub genes were validated using quantitative RT-qPCR and clinical data. DSigDB database predicted potential therapeutic agents.

RESULTS

Seven hub genes (IFI44, IFI44L, MX1, OAS3, USP18, IFI27, and ISG15) were potential biomarkers for Omicron infection's symptomatic diagnosis and treatment. Type I interferon-related hub genes regulated Omicron-induced symptoms, which is supported by independent datasets and RT-qPCR validation. Immune cell analysis showed elevated monocytes and reduced lymphocytes in COVID-19 patients, which is consistent with retrospective clinical data. Additionally, ten potential therapeutic agents were screened for COVID-19 treatment, targeting the hub genes.

CONCLUSIONS

This study provides insights into the mechanisms underlying type I interferon-related pathways in the development and recovery of COVID-19 symptoms during Omicron infection. Seven hub genes were identified as promising biological biomarkers for diagnosing and treating Omicron infection. The identified biomarkers and potential therapeutic agent offer valuable implications for Omicron's clinical manifestations and treatment strategies.

Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren's syndrome based on integrated bioinformatics and single-cell RNA-seq analysis

Background

Systemic lupus erythematosus (SLE) and primary Sjögren's syndrome (pSS) are common systemic autoimmune diseases that share a wide range of clinical manifestations and serological features. This study investigates genes, signaling pathways, and transcription factors (TFs) shared between SLE and pSS.

Methods

Gene expression profiles of SLE and pSS were obtained from the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to identify shared genes related to SLE and pSS. Overlapping genes were then subject to Gene Ontology (GO) and protein-protein interaction (PPI) network analyses. Cytoscape plugins cytoHubba and iRegulon were subsequently used to screen shared hub genes and predict TFs. In addition, gene set variation analysis (GSVA) and CIBERSORTx were used to calculate the correlations between hub genes and immune cells as well as related pathways. To confirm these results, hub genes and TFs were verified in microarray and single-cell RNA sequencing (scRNA-seq) datasets.

Results

Following WGCNA and limma analysis, 152 shared genes were identified. These genes were involved in interferon (IFN) response and cytokine-mediated signaling pathway. Moreover, we screened six shared genes, namely IFI44L, ISG15, IFIT1, USP18, RSAD2 and ITGB2, out of which three genes, namely IFI44L, ISG15 and ITGB2 were found to be highly expressed in both microarray and scRNA-seq datasets. IFN response and ITGB2 signaling pathway were identified as potentially relevant pathways. In addition, STAT1 and IRF7 were identified as common TFs in both diseases.

Conclusion

This study revealed IFI44L, ISG15 and ITGB2 as the shared genes and identified STAT1 and IRF7 as the common TFs of SLE and pSS. Notably, the IFN response and ITGB2 signaling pathway played vital roles in both diseases. Our study revealed common pathogenetic characteristics of SLE and pSS. The particular roles of these pivotal genes and mutually overlapping pathways may provide a basis for further mechanistic research.

Systemic lupus erythematosus: From non-coding RNAs to exosomal non-coding RNAs

Systemic lupus erythematosus (SLE), as an immunological illness, frequently impacts young females. Both vulnerabilities to SLE and the course of the illness's clinical symptoms have been demonstrated to be affected by individual differences in non-coding RNA expression. Many non-coding RNAs (ncRNAs) are out of whack in patients with SLE. Because of the dysregulation of several ncRNAs in peripheral blood of patients suffering from SLE, these ncRNAs to be showed valuable as biomarkers for medication response, diagnosis, and activity. NcRNAs have also been demonstrated to influence immune cell activity and apoptosis. Altogether, these facts highlight the need of investigating the roles of both families of ncRNAs in the progress of SLE. Being aware of the significance of these transcripts perhaps elucidates the molecular pathogenesis of SLE and could open up promising avenues to create tailored treatments during this condition. In this review we summarized various non-coding RNAs and Exosomal non-coding RNAs in SLE.

Novel polymorphism of IFI44L associated with the susceptibility and clinical characteristics of systemic lupus erythematosus in a Chinese population

BACKGROUND

Interferon-inducible 44 like (IFI44L) is a newly discovered gene which has been reported to associate with the susceptibility of some infectious diseases, but there is no data on IFI44L SNP polymorphism associated with Systemic lupus erythematosus (SLE). In this study, we aimed to evaluate the association of IFI44L rs273259 polymorphism with the susceptibility and clinical characteristics of SLE in a Chinese population.

METHODS

576 SLE patients and 600 controls were recruited in this case-control study. Blood DNA was extracted and IFI44L rs273259 polymorphism was detected by TaqMan SNP Genotyping Assay Kit. The expression levels of IFI44L in Peripheral blood mononuclear cells were detected by RT-qPCR. The DNA methylation levels of IFI44L promoter were detected by bisulfite pyrosequencing.

RESULTS

The genotype and allele frequencies of IFI44L rs273259 in SLE patients have a significantly difference compared to healthy controls (P < 0.001). The genotype AG (vs. AA: OR = 2.849; P < 0.001) and the allele G (vs. A: OR = 1.454; P < 0.001) were associated with increased susceptibility of SLE. IFI44L rs273259 polymorphism was associated with clinical characteristics of SLE including malar rash (P < 0.001), discoid rash (P < 0.001), lupus nephritis (P < 0.001) and anti-Smith antibodies (P < 0.001). The expression levels of IFI44L were most significantly increased in genotype AG than genotype AA and GG (P < 0.01). The DNA methylation levels of IFI44L promoter were most significantly decreased in genotype AG than genotype AA and GG (P < 0.01).

CONCLUSIONS

Our results indicate novel polymorphism of IFI44L rs273259 was associated with the susceptibility and clinical characteristics of SLE in the Chinese population.

DNA methylation alterations in systemic lupus erythematosus: A systematic review of case-control studies

BACKGROUND

Traditionally, the diagnosis and monitoring of disease activity in systemic lupus erythematosus (SLE) are contingent upon clinical manifestations and serological markers. However, researchers are struggling to find biomarkers with higher sensitivity and specificity. DNA methylation has been the most studied epigenetic feature in SLE. So, in this study, we performed a systematic review of studies about DNA methylation alterations in SLE patients compared to healthy controls.

METHODS

By searching PubMed, Scopus, and Google Scholar up to July 2022, all case-control studies in which DNA methylation of specific genes was assessed by a non-high-throughput technique and passed the quality of bias assessment were included.

RESULTS

In total, 44 eligible studies underwent a data extraction process. In all, 3471 SLE patients and 1028 healthy individuals were included. Among the studies that reported the patients' gender (n = 2853), 89.41% were female and 10.59% were male. Forty studies have been conducted on adult patients. The number of works on fractionated and unfractionated blood cells was almost equal. In this regard, 22 studies were conducted on whole blood or peripheral blood mononuclear cells and two studies on unfractionated white blood cells. Sorted blood cells were biological sources in 20 studies. The most investigated gene was IFI44L. Sensitivity, specificity, and diagnostic power of methylation levels were only reported for IFI44L in five studies. The most employed methylation profiling method was bisulfite sequencing polymerase chain reaction. The correlation between methylation patterns and clinical parameters was explored in 22 studies, which of them 16 publications displayed a remarkable association between DNA methylation status and clinical indices.

CONCLUSIONS

The methylation status of some genes especially IFI44L, FOXP3, and MX1 has been suggested as promising SLE biomarkers. However, given the conflicting findings between studies because of potential confounders such as different sample types, methylation profiling methods, and ethnicity as well as shared DNA methylation patterns of SLE and other autoimmune diseases, DNA methylation biomarkers are currently not reliable diagnostic biomarkers and do not represent surrogate markers of SLE disease activity. Future investigations on a larger scale with the discarding of limitations of previous studies would probably lead to a consensus.

Type I interferon pathway assays in studies of rheumatic and musculoskeletal diseases: a systematic literature review informing EULAR points to consider

OBJECTIVES

To systematically review the literature for assay methods that aim to evaluate type I interferon (IFN-I) pathway activation and to harmonise-related terminology.

METHODS

Three databases were searched for reports of IFN-I and rheumatic musculoskeletal diseases. Information about the performance metrics of assays measuring IFN-I and measures of truth were extracted and summarised. A EULAR task force panel assessed feasibility and developed consensus terminology.

RESULTS

Of 10 037 abstracts, 276 fulfilled eligibility criteria for data extraction. Some reported more than one technique to measure IFN-I pathway activation. Hence, 276 papers generated data on 412 methods. IFN-I pathway activation was measured using: qPCR (n=121), immunoassays (n=101), microarray (n=69), reporter cell assay (n=38), DNA methylation (n=14), flow cytometry (n=14), cytopathic effect assay (n=11), RNA sequencing (n=9), plaque reduction assay (n=8), Nanostring (n=5), bisulphite sequencing (n=3). Principles of each assay are summarised for content validity. Concurrent validity (correlation with other IFN assays) was presented for n=150/412 assays. Reliability data were variable and provided for 13 assays. Gene expression and immunoassays were considered most feasible. Consensus terminology to define different aspects of IFN-I research and practice was produced.

CONCLUSIONS

Diverse methods have been reported as IFN-I assays and these differ in what elements or aspects of IFN-I pathway activation they measure and how. No 'gold standard' represents the entirety of the IFN pathway, some may not be specific for IFN-I. Data on reliability or comparing assays were limited, and feasibility is a challenge for many assays. Consensus terminology should improve consistency of reporting.

Association between type I interferon pathway activation and clinical outcomes in rheumatic and musculoskeletal diseases: a systematic literature review informing EULAR points to consider

BACKGROUND

Type I interferons (IFN-I) contribute to a broad range of rheumatic and musculoskeletal diseases (RMDs). Compelling evidence suggests that the measurement of IFN-I pathway activation may have clinical value. Although several IFN-I pathway assays have been proposed, the exact clinical applications are unclear. We summarise the evidence on the potential clinical utility of assays measuring IFN-I pathway activation.

METHODS

A systematic literature review was conducted across three databases to evaluate the use of IFN-I assays in diagnosis and monitor disease activity, prognosis, response to treatment and responsiveness to change in several RMDs.

RESULTS

Of 366 screened, 276 studies were selected that reported the use of assays reflecting IFN-I pathway activation for disease diagnosis (n=188), assessment of disease activity (n=122), prognosis (n=20), response to treatment (n=23) and assay responsiveness (n=59). Immunoassays, quantitative PCR (qPCR) and microarrays were reported most frequently, while systemic lupus erythematosus (SLE), rheumatoid arthritis, myositis, systemic sclerosis and primary Sjögren's syndrome were the most studied RMDs. The literature demonstrated significant heterogeneity in techniques, analytical conditions, risk of bias and application in diseases. Inadequate study designs and technical heterogeneity were the main limitations. IFN-I pathway activation was associated with disease activity and flare occurrence in SLE, but their incremental value was uncertain. IFN-I pathway activation may predict response to IFN-I targeting therapies and may predict response to different treatments.

CONCLUSIONS

Evidence indicates potential clinical value of assays measuring IFN-I pathway activation in several RMDs, but assay harmonisation and clinical validation are urged. This review informs the EULAR points to consider for the measurement and reporting of IFN-I pathway assays.

The critical importance of epigenetics in autoimmune-related skin diseases

Autoimmune-related skin diseases are a group of disorders with diverse etiology and pathophysiology involved in autoimmunity. Genetics and environmental factors may contribute to the development of these autoimmune disorders. Although the etiology and pathogenesis of these disorders are poorly understood, environmental variables that induce aberrant epigenetic regulations may provide some insights. Epigenetics is the study of heritable mechanisms that regulate gene expression without changing DNA sequences. The most important epigenetic mechanisms are DNA methylation, histone modification, and noncoding RNAs. In this review, we discuss the most recent findings regarding the function of epigenetic mechanisms in autoimmune-related skin disorders, including systemic lupus erythematosus, bullous skin diseases, psoriasis, and systemic sclerosis. These findings will expand our understanding and highlight the possible clinical applications of precision epigenetics approaches.

Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease with strong heterogeneity, leading to variable clinical symptoms, which makes diagnosis and activity evaluation difficult.

Methods

The original dataset of GSE88884 was analyzed to screen differentially expressed genes (DEGs) of SLE and the correlation between DEGs and clinical parameters (SLEDAI, anti-dsDNA, C3, and C4). The result was validated by microarray GSE121239 and SLE patients with RT-qPCR. Next, receiver operator characteristic (ROC) analysis, correlation analysis, and ordinal logistic regression were applied, respectively, to evaluate the capability of diagnosis and prediction of the candidate biomarker. Subsequently, the biological functions of the candidate biomarker were investigated through KEGG and GO enrichment, protein-protein interaction network, and the correlation matrix.

Results

A total of 283 DEGs were screened, and seven of them were overlapped with SLE-related genes. DDX60 was identified as the candidate biomarker. Analyses of GSE88884, GSE121239, and SLE patients with RT-qPCR indicated that DDX60 expression level is significantly higher in patients with high disease activity. ROC analysis and the area under the ROC curve (AUC = 0.8818) suggested that DDX60 has good diagnostic performance. DDX60 expression level was positively correlated with SLEDAI scores (r = 0.24). For every 1-unit increase in DDX60 expression value, the odds of a higher stage of activity of SLE disease are multiplied by 1.47. The function of DDX60 mainly focuses on IFN-I-induced antiviral activities, RIG-I signaling, and innate immune. Moreover, DDX60 plays a synergistic role with DDX58, IFIH1, OASL, IFIT1, and other related genes in the SLE pathogenesis. Conclusions. DDX60 is differently expressed in SLE, and it is significantly related to both serological indicators and the disease activity of SLE. We suggested that DDX60 might be a potential biomarker for SLE diagnosis and management.

Identification of potential biomarkers for systemic lupus erythematosus by integrated analysis of gene expression and methylation data

INTRODUCTION

Systemic lupus erythematosus (SLE) is a heterogeneous and chronic autoimmune disease. Aberrant DNA methylation occurs during various processes of SLE development regulating the mRNA expression of interrelated genes. This study aims to screen potential DNA methylation markers for SLE.

METHODS

Gene expression and methylation datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between SLE patients and healthy controls were screened using the limma R package, and differentially methylated positions (DMPs) and regions (DMRs) were identified using dmpfinder and bumphunter (minfi). Additionally, the DNA methylation markers to distinguish SLE patients from healthy controls were explored through receiver operating characteristic (ROC) curves and logistic regression analyses. Finally, we validated the results of the bioinformatic analysis by pyrosequencing.

RESULTS

In total, 91 DEGs, 90,092 DMPs, 15 DMRs, and 13 DMR-associated genes were identified. Through the integrative analysis of DEG- and DMR-associated genes, we identified five type I interferon (IFN)-related genes as key epigenetic-driven genes in SLE. GO enrichment analysis showed that the five SLE-associated epigenetic-driven genes were mainly enriched in the type I IFN signaling pathway involved in immune response and defense response to virus. Moreover, we identified two SLE-specific DNA methylation markers, three SLE without lupus nephritis (SLE-LN^-)-specific DNA methylation markers, and two SLE with lupus nephritis (SLE-LN⁺)-specific DNA methylation markers by stepwise logistic regression.

CONCLUSIONS

Overall, our study demonstrates potential DNA methylation markers of SLE, SLE-LN^-, and SLE-LN⁺, which may help the diagnosis, boost the development of new epigenetic therapy, and contribute to individualized treatment. Key Points • This study identified five type I IFN-related genes as key epigenetic-driven genes in SLE, which support the importance of the type I IFN pathway in the pathogenesis of SLE • We identified novel DNA methylation biomarkers in SLE, SLE-LN-, and SLE-LN+ by a comprehensive analysis of bioinformatics methods and executed experimental validation, and binary logistic regression analysis showed that they have excellent potential • These results may provide new insights into the biological mechanisms of SLE, and identify reliable biomarkers for SLE, SLE-LN-, and SLE-LN+, which may contribute to diagnosis and individualized treatment.

Differential diagnosis of systemic lupus erythematosus and Sjögren's syndrome using machine learning and multi-omics data

Systemic lupus erythematosus and primary Sjogren's syndrome are complex systemic autoimmune diseases that are often misdiagnosed. In this article, we demonstrate the potential of machine learning to perform differential diagnosis of these similar pathologies using gene expression and methylation data from 651 individuals. Furthermore, we analyzed the impact of the heterogeneity of these diseases on the performance of the predictive models, discovering that patients assigned to a specific molecular cluster are misclassified more often and affect to the overall performance of the predictive models. In addition, we found that the samples characterized by a high interferon activity are the ones predicted with more accuracy, followed by the samples with high inflammatory activity. Finally, we identified a group of biomarkers that improve the predictions compared to using the whole data and we validated them with external studies from other tissues and technological platforms.

An update on epigenetic regulation in autoimmune diseases

Autoimmune diseases (AIDs) generally manifest as chronic immune disorders characterized by significant heterogeneity and complex symptoms. The discordant incidence of AIDs between monozygotic twins guided people to attach importance to environmental factors. Epigenetics is one of the major ways to be influenced, some of them can even occur years before clinical diagnosis. With the advent of high-throughput omics times, the mysterious veil of epigenetic modification in AIDs has been gradually unraveled, and some progress has been made in utilizing it as indicators of diagnosis and disease activity. For example, the hypomethylated IFI44L promoter in diagnosing systematic lupus erythematosus (SLE). More recently, newly identified noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs), are also believed to be involved in the etiology of AIDs while the initial factor behind those epigenetic alterations can be diverse from metabolism to microbiota. Update and comprehensive insights into epigenetics in AIDs can help us understand the pathogenesis and further orchestrate it to benefit patients in the future. Therefore, we reviewed the latest epigenetic findings in SLE, rheumatoid arthritis (RA), Type 1 diabetes (T1D), systemic sclerosis (SSc) primarily from cellular levels.

Predicting diagnostic gene expression profiles associated with immune infiltration in patients with lupus nephritis

Objective

To identify potential diagnostic markers of lupus nephritis (LN) based on bioinformatics and machine learning and to explore the significance of immune cell infiltration in this pathology.

Methods

Seven LN gene expression datasets were downloaded from the GEO database, and the larger sample size was used as the training group to obtain differential genes (DEGs) between LN and healthy controls, and to perform gene function, disease ontology (DO), and gene set enrichment analyses (GSEA). Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to identify candidate biomarkers. The diagnostic value of LN diagnostic gene biomarkers was further evaluated in the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from LN patients and to analyze their correlation with diagnostic markers.

Results

Thirty and twenty-one DEGs were screened in kidney tissue and peripheral blood, respectively. Both of which covered macrophages and interferons. The disease enrichment analysis of DEGs in kidney tissues showed that they were mainly involved in immune and renal diseases, and in peripheral blood it was mainly enriched in cardiovascular system, bone marrow, and oral cavity. The machine learning algorithm combined with external dataset validation revealed that C1QA(AUC = 0.741), C1QB(AUC = 0.758), MX1(AUC = 0.865), RORC(AUC = 0.911), CD177(AUC = 0.855), DEFA4(AUC= 0.843)and HERC5(AUC = 0.880) had high diagnostic value and could be used as diagnostic biomarkers of LN. Compared to controls, pathways such as cell adhesion molecule cam, and systemic lupus erythematosus were activated in kidney tissues; cell cycle, cytoplasmic DNA sensing pathways, NOD-like receptor signaling pathways, proteasome, and RIG-1-like receptors were activated in peripheral blood. Immune cell infiltration analysis showed that diagnostic markers in kidney tissue were associated with T cells CD8 and Dendritic cells resting, and in blood were associated with T cells CD4 memory resting, suggesting that CD4 T cells, CD8 T cells and dendritic cells are closely related to the development and progression of LN.

Conclusion

C1QA, C1QB, MX1, RORC, CD177, DEFA4 and HERC5 could be used as new candidate molecular markers for LN. It may provide new insights into the diagnosis and molecular treatment of LN in the future.

Epigenetic regulation of B cells and its role in autoimmune pathogenesis

B cells play a pivotal role in the pathogenesis of autoimmune diseases. Although previous studies have shown many genetic polymorphisms associated with B-cell activation in patients with various autoimmune disorders, progress in epigenetic research has revealed new mechanisms leading to B-cell hyperactivation. Epigenetic mechanisms, including those involving histone modifications, DNA methylation, and noncoding RNAs, regulate B-cell responses, and their dysregulation can contribute to the pathogenesis of autoimmune diseases. Patients with autoimmune diseases show epigenetic alterations that lead to the initiation and perpetuation of autoimmune inflammation. Moreover, many clinical and animal model studies have shown the promising potential of epigenetic therapies for patients. In this review, we present an up-to-date overview of epigenetic mechanisms with a focus on their roles in regulating functional B-cell subsets. Furthermore, we discuss epigenetic dysregulation in B cells and highlight its contribution to the development of autoimmune diseases. Based on clinical and preclinical evidence, we discuss novel epigenetic biomarkers and therapies for patients with autoimmune disorders.

Progress in the application of body fluid and tissue level mRNAs-non-coding RNAs for the early diagnosis and prognostic evaluation of systemic lupus erythematosus

The diagnosis and differential classification of systemic lupus erythematosus (SLE) is difficult, especially in patients with early-onset SLE who are susceptible to systemic multi-organ damage and serious complications and have difficulties in individualized treatment. At present, diagnosis is based mainly on clinical manifestations and the detection of serological antinuclear antibodies. The pathogenesis of SLE involves multiple factors, is clinically heterogeneous, and lacks specific biomarkers. Therefore, it is necessary to identify new biomarkers for the diagnosis and subtype classification of SLE. Non-coding RNAs (ncRNAs) are composed of microRNAs, long non-coding RNAs, small nucleolar RNAs, circular RNAs, and transfer RNAs. They play an important role in the occurrence and development of diseases and are used widely in the early diagnosis and prognosis of autoimmune diseases. In this review, we focus on the research progress in the diagnosis and prognostic assessment of SLE using humoral to tissue level ncRNAs.

Altered B cell phenotype and CD27+ memory B cells are associated with clinical features and environmental exposure in Colombian systemic lupus erythematosus patients

Background

B lymphocytes are dysregulated in Systemic Lupus Erythematosus (SLE) including the expansion of extrafollicular B cells in patients with SLE of African American ancestry, which is associated with disease activity and nephritis. The population of Colombia has a mixture of European, Native American, and African ancestry. It is not known if Colombian patients have the same B cell distributions described previously and if they are associated with disease activity, clinical manifestations, and environmental exposures.

Objective

To characterize B cell phenotype in a group of Colombian Systemic Lupus Erythematosus patients with mixed ancestry and determine possible associations with disease activity, clinical manifestations, the DNA methylation status of the IFI44L gene and environmental exposures.

Materials and methods

Forty SLE patients and 17 healthy controls were recruited. Cryopreserved peripheral B lymphocytes were analyzed by multiparameter flow cytometry, and the DNA methylation status of the gene IFI44L was evaluated in resting Naive B cells (rNAV).

Results

Extrafollicular active Naive (aNAV) and Double Negative type 2, DN2 (CD27− IgD− CD21− CD11c+) B cells were expanded in severe active patients and were associated with nephritis. Patients had hypomethylation of the IFI44L gene in rNAV cells. Regarding environmental exposure, patients occupationally exposed to organic solvents had increased memory CD27+ cells (SWM).

Conclusion

aNAV and DN2 extrafollicular cells showed significant clinical associations in Colombian SLE patients, suggesting a relevant role in the disease’s pathophysiology. Hypomethylation of the IFI44L gene in resting Naive B cells suggests that epigenetic changes are established at exceedingly early stages of B cell ontogeny. Also, an alteration in SWM memory cells was observed for the first time in patients exposed to organic solvents. This opens different clinical and basic research possibilities to corroborate these findings and deepen the knowledge of the relationship between environmental exposure and SLE.

Transcriptome innovations in primates revealed by single-molecule long-read sequencing

Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Around half of the captured isoforms are not annotated in their reference genomes, significantly expanding the gene models in primates. Furthermore, our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these evolutionary innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.