Revealing the Immune Heterogeneity between Systemic Lupus Erythematosus and Rheumatoid Arthritis Based on Multi-Omics Data Analysis

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

Comprehensive analysis of juvenile idiopathic arthritis patients' immune characteristics based on bulk and single-cell sequencing data

Background

The pathogenesis of juvenile idiopathic arthritis (JIA) is strongly influenced by an impaired immune system. However, the molecular mechanisms underlying its development and progression have not been elucidated. In this study, the computational methods TRUST4 were used to construct a T-cell receptor (TCR) and B-cell receptor (BCR) repertoire from the peripheral blood of JIA patients via bulk RNA-seq data, after which the clonality and diversity of the immune repertoire were analyzed.

Results

Our findings revealed significant differences in the frequency of clonotypes between the JIA and healthy control groups in terms of the TCR and BCR repertoires. This work identified specific V genes and J genes in TCRs and BCRs that could be used to expand our understanding of JIA. After single-cell RNA analysis, the relative percentages of CD14 monocytes were significantly greater in the JIA group. Cell-cell communication analysis revealed the significant role of the MIF signaling pathway in JIA.

Conclusion

In conclusion, this work describes the immune features of both the TCR and BCR repertoires under JIA conditions and provides novel insight into immunotherapy for JIA.

Exploring the therapeutic potential of regulatory T cell in rheumatoid arthritis: Insights into subsets, markers, and signaling pathways

Rheumatoid arthritis (RA) is a complex autoimmune inflammatory rheumatic disease characterized by an imbalance between immunological reactivity and immune tolerance. Regulatory T cells (Tregs), which play a crucial role in controlling ongoing autoimmunity and maintaining peripheral tolerance, have shown great potential for the treatment of autoimmune inflammatory rheumatic diseases such as RA. This review aims to provide an updated summary of the latest insights into Treg-targeting techniques in RA. We focus on current therapeutic strategies for targeting Tregs based on discussing their subsets, surface markers, suppressive function, and signaling pathways in RA.

B-1 derived anti-Thy-1 B cells in old aged mice develop lymphoma/leukemia with high expression of CD11b and Hamp2 that different from TCL1 transgenic mice

Human old aged unmutated chronic lymphocytic leukemia U-CLL are the TCL1+ZAP70+CD5+ B cells. Since CD5 makes the BCR signaling tolerance, ZAP70 increased in U-CLL not only TCL1+ alone. In mice, TCL1 (TCL1A) is the negative from neonate to old aged, as TC-. VH8-12/Vk21-5 is the anti-thymocyte/Thy-1 autoreactive ATA B cell. When ATA μκTg generation in mice, ATA B cells are the neonate generated CD5+ B cells in B-1, and in the middle age, CD5+ can be down or continuously CD5+, then, old aged CLL/lymphoma generation with increased CD11b in TC-ZAP70-CD5- or TC-ZAP70+CD5+. In this old aged TC-ATA B microarray analysis showed most similar to human CLL and U-CLL, and TC-ZAP70+CD5+ showed certain higher present as U-CLL. Original neonate ATA B cells showed with several genes down or further increase in old aged tumor, and old aged T-bet+CD11c+, CTNNB1hi, HMGBhi, CXCR4hi, DPP4hi and decreased miR181b. These old aged increased genes and down miR181b are similar to human CLL. Also, in old age ATA B cell tumor, high CD38++CD44++, increased Ki67+ AID+, and decreased CD180- miR15Olow are similar to U-CLL. In this old aged ATA B, increased TLR7,9 and Wnt10b. TC+Tg generated with ATAμκTg mice occurred middle age tumor as TC+ZAP70-CD5+ or TC+ZAP70+CD5+, with high NF-kB1, TLR4,6 and Wnt5b,6 without increased CD11b. Since neonatal state to age with TC+Tg continuously, middle age CLL/lymphoma generation is not similar to old aged generated, however, some increased in TC+ZAP70+ are similar to the old age TC- ATA B tumor. Then, TC- ATA B old age tumor showed some difference to human CLL. ATA B cells showed CD11b+CD22++, CD24 down, and hepcidin Hamp2++ with iron down. This mouse V8-12 similar to human V2-5, and V2-5 showed several cancers with macrophages/neutrophils generated hepcidin+ ironlow or some showed hepcidin- iron+ with tumor, and mouse V8-12 with different Vk19-17 generate MZ B cells strongly increased macrophage++ in old aged and generated intestine/colon tumor. Conclusion, neonate generated TC-ATA B1 cells in old aged tumor generation are CD11b+ in the leukemia CLL together with lymphoma cancer with hepcidin-related Hamp2++ in B-1 cell generation to control iron.

Loss of TET2 increases B-1 cell number and IgM production while limiting CDR3 diversity

Recent studies have demonstrated a role for Ten-Eleven Translocation-2 (TET2), an epigenetic modulator, in regulating germinal center formation and plasma cell differentiation in B-2 cells, yet the role of TET2 in regulating B-1 cells is largely unknown. Here, B-1 cell subset numbers, IgM production, and gene expression were analyzed in mice with global knockout of TET2 compared to wildtype (WT) controls. Results revealed that TET2-KO mice had elevated numbers of B-1a and B-1b cells in their primary niche, the peritoneal cavity, as well as in the bone marrow (B-1a) and spleen (B-1b). Consistent with this finding, circulating IgM, but not IgG, was elevated in TET2-KO mice compared to WT. Analysis of bulk RNASeq of sort purified peritoneal B-1a and B-1b cells revealed reduced expression of heavy and light chain immunoglobulin genes, predominantly in B-1a cells from TET2-KO mice compared to WT controls. As expected, the expression of IgM transcripts was the most abundant isotype in B-1 cells. Yet, only in B-1a cells there was a significant increase in the proportion of IgM transcripts in TET2-KO mice compared to WT. Analysis of the CDR3 of the BCR revealed an increased abundance of replicated CDR3 sequences in B-1 cells from TET2-KO mice, which was more clearly pronounced in B-1a compared to B-1b cells. V-D-J usage and circos plot analysis of V-J combinations showed enhanced usage of VH11 and VH12 pairings. Taken together, our study is the first to demonstrate that global loss of TET2 increases B-1 cell number and IgM production and reduces CDR3 diversity, which could impact many biological processes and disease states that are regulated by IgM.

Inhibition of IL-17 signaling in macrophages underlies the anti-arthritic effects of halofuginone hydrobromide: Network pharmacology, molecular docking, and experimental validation

BACKGROUND

Rheumatoid arthritis (RA) is a prevalent autoimmune disease marked by chronic synovitis as well as cartilage and bone destruction. Halofuginone hydrobromide (HF), a bioactive compound derived from the Chinese herbal plant Dichroa febrifuga Lour., has demonstrated substantial anti-arthritic effects in RA. Nevertheless, the molecular mechanisms responsible for the anti-RA effects of HF remain unclear.

METHODS

This study employed a combination of network pharmacology, molecular docking, and experimental validation to investigate potential targets of HF in RA.

RESULTS

Network pharmacology analyses identified 109 differentially expressed genes (DEGs) resulting from HF treatment in RA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses unveiled a robust association between these DEGs and the IL-17 signaling pathway. Subsequently, a protein-protein interaction (PPI) network analysis revealed 10 core DEGs, that is, EGFR, MMP9, TLR4, ESR1, MMP2, PPARG, MAPK1, JAK2, STAT1, and MAPK8. Among them, MMP9 displayed the greatest binding energy for HF. In an in vitro assay, HF significantly inhibited the activity of inflammatory macrophages, and regulated the IL-17 signaling pathway by decreasing the levels of IL-17 C, p-NF-κB, and MMP9.

CONCLUSION

In summary, these findings suggest that HF has the potential to inhibit the activation of inflammatory macrophages through its regulation of the IL-17 signaling pathway, underscoring its potential in the suppression of immune-mediated inflammation in RA.

Multiomics Data Reveal the Important Role of ANXA2R in T Cell-mediated Rejection After Renal Transplantation

BACKGROUND

T cell-mediated rejection (TCMR) is a severe issue after renal transplantation, but research on its T cell-receptor (TCR) repertoire is lacking. This study intended to elucidate the TCR repertoire landscape in TCMR and hence identify novel potential targets.

METHODS

A total of 12 multiomics data sets were collected. The TRUST4 algorithm was used to construct and analyze the TCR repertoire in renal allografts with TCMR and stable renal function. Then, novel TCR-related key genes were identified through various criteria and literature research. In bulk transcriptome, cell line, single-cell transcriptome data sets, multiple immune cell infiltration algorithms, and gene set enrichment analysis were used to analyze potential mechanisms of the identified key gene. Twenty-three pathological sections were collected for immunofluorescence staining in the clinical cohort. Finally, the diagnostic and prognostic values of ANXA2R were evaluated in multiple renal transplant data sets.

RESULTS

Allografts with TCMR showed significantly increased clonotype and specific clonal expansion. ANXA2R was found to be a novel key gene for TCMR and showed strong positive connections with the TCR complex and lymphocyte cells, especially CD8 + T cells. Immunofluorescence staining confirmed the existence of ANXA2R + CD8 + T cells, with their percentage significantly elevated in TCMR compared with stable renal function. Finally, both mRNA and protein levels of ANXA2R showed promising diagnostic and prognostic value for renal transplant recipients.

CONCLUSIONS

ANXA2R , identified as a novel TCR-related gene, had critical roles in clinicopathology, diagnosis, and prognosis in renal transplantation, which offered promising potential therapeutic targets.

B-Cell Receptor Repertoire: Recent Advances in Autoimmune Diseases

In the field of contemporary medicine, autoimmune diseases (AIDs) are a prevalent and debilitating group of illnesses. However, they present extensive and profound challenges in terms of etiology, pathogenesis, and treatment. A major reason for this is the elusive pathophysiological mechanisms driving disease onset. Increasing evidence suggests the indispensable role of B cells in the pathogenesis of autoimmune diseases. Interestingly, B-cell receptor (BCR) repertoires in autoimmune diseases display a distinct skewing that can provide insights into disease pathogenesis. Over the past few years, advances in high-throughput sequencing have provided powerful tools for analyzing B-cell repertoire to understand the mechanisms during the period of B-cell immune response. In this paper, we have provided an overview of the mechanisms and analytical methods for generating BCR repertoire diversity and summarize the latest research progress on BCR repertoire in autoimmune diseases, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), primary Sjögren's syndrome (pSS), multiple sclerosis (MS), and type 1 diabetes (T1D). Overall, B-cell repertoire analysis is a potent tool to understand the involvement of B cells in autoimmune diseases, facilitating the creation of innovative therapeutic strategies targeting specific B-cell clones or subsets.

B cell receptor repertoire abnormalities in autoimmune disease

B cells play a crucial role in the immune response and contribute to various autoimmune diseases. Recent studies have revealed abnormalities in the B cell receptor (BCR) repertoire of patients with autoimmune diseases, with distinct features observed among different diseases and B cell subsets. Classically, BCR repertoire was used as an identifier of distinct antigen-specific clonotypes, but the recent advancement of analyzing large-scale repertoire has enabled us to use it as a tool for characterizing cellular biology. In this review, we provide an overview of the BCR repertoire in autoimmune diseases incorporating insights from our latest research findings. In systemic lupus erythematosus (SLE), we observed a significant skew in the usage of VDJ genes, particularly in CD27+IgD+ unswitched memory B cells and plasmablasts. Notably, autoreactive clones within unswitched memory B cells were found to be increased and strongly associated with disease activity, underscoring the clinical significance of this subset. Similarly, various abnormalities in the BCR repertoire have been reported in other autoimmune diseases such as rheumatoid arthritis. Thus, BCR repertoire analysis holds potential for enhancing our understanding of the underlying mechanisms involved in autoimmune diseases. Moreover, it has the potential to predict treatment effects and identify therapeutic targets in autoimmune diseases.

The clinical applications of immunosequencing

Technological advances in high-throughput sequencing have opened the door for the interrogation of adaptive immune responses at unprecedented scale. It is now possible to determine the sequences of antibodies or T-cell receptors produced by individual B and T cells in a sample. This capability, termed immunosequencing, has transformed the study of both infectious and non-infectious diseases by allowing the tracking of dynamic changes in B and T cell clonal populations over time. This has improved our understanding of the pathology of cancers, autoimmune diseases, and infectious diseases. However, to date there has been only limited clinical adoption of the technology. Advances over the last decade and on the horizon that reduce costs and improve interpretability could enable widespread clinical use. Many clinical applications have been proposed and, while most are still undergoing research and development, some methods relying on immunosequencing data have been implemented, the most widespread of which is the detection of measurable residual disease. Here, we review the diagnostic, prognostic, and therapeutic applications of immunosequencing for both infectious and non-infectious diseases.

Effect of BAFF blockade on the B cell receptor repertoire and transcriptome in a mouse model of systemic lupus erythematosus

Introduction

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Anti-B-cell-activating factor (BAFF) therapy effectively depletes B cells and reduces SLE disease activity. This research aimed to evaluate the effect of BAFF blockade on B cell receptor (BCR) repertoire and gene expression.

Methods

Through next-generation sequencing, we analyzed gene expression and BCR repertoire in MRL/lpr mice that received long-term anti-BAFF therapy. Based on gene expression profiles, we predicted the relative proportion of immune cells using ImmuCellAI-mouse, validating our predictions via flow cytometry and FluoroSpot.

Results

The loss of BCR repertoire diversity and richness, along with increased clonality and differential frequency distribution of the immunoglobulin heavy chain variable (IGHV) segment gene usage, were observed in BAFF-blockade mice. Meanwhile, the distribution of complementarity-determining region 3 (CDR3) length and CDR3 amino acid usage remained unaffected. BAFF blockade resulted in extensive changes in gene expression, particularly that of genes related to B cells and immunoglobulins. Besides, the tumor necrosis factor (TNF)-α responses and interferon (IFN)-α/γ were downregulated, consistent with the decrease in IFN-γ and TNF-α serum levels following anti-BAFF therapy. In addition, BAFF blockade significantly reduced B cell subpopulations and plasmacytoid dendritic cells, and caused the depletion of antibody-secreting cells.

Discussion

Our comparative BCR repertoire and transcriptome analyses of MRL/lpr mice subjected to BAFF blockade provide innovative insights into the molecular pathophysiology of SLE.

A comprehensive exploration of the heterogeneity of immune cells in Han and Zang systemic lupus erythematosus patients via single-cell RNA sequencing

Systemic Lupus Erythematosus (SLE) is an autoimmune sickness with unclear pathogenesis. The goal of this research was to reveal the heterogeneity of immune cells in SLE patients of Han and Zang nationality by single-cell RNA sequencing (scRNA-seq) and bioinformatics profiling.

METHODS

A total of 94,102 peripheral blood mononuclear cells (PBMCs) from six volunteers with SLE (3 Zang, 3 Han) and six healthy controls were first conducted through scRNA-seq analysis. The immune cell subsets in the pathogenesis of SLE were analyzed as well. Real-time quantitative PCR (RT-qPCR) was applied to confirm the results of sc-RNA seq analysis.

RESULTS

For the Tibetan samples, the ratios of Naïve CD4 RPS4Y1 cells, Naïve CD4 cells, Memory BC CD24 and Memory BC differed significantly between the SLE and control samples, while that of CD8 CTL MAL cells was significantly different between the two groups in Han nationality samples. Variable differentiation states of CD8 CTL MAL cells, CD8 CTL GZMK cells, and Naïve CD4 cells were detected through pseudotime analysis. Moreover, T-cell receptor (TCR) abundance was notably higher in Tibetan SLE specimens than that in controls, while B-cell receptor (BCR) abundance in Tibetan and Han samples was higher than in control groups.

CONCLUSIONS

In summary, the immune cellular heterogeneity of SLE patients both Han and Zang nationality was explored based on various bioinformatics approaches, providing new perspectives for immunological characteristics of SLE among different ethnic groups.

A Peripheral Blood Signature of Increased Th1 and Myeloid Cells Combined with Serum Inflammatory Mediators Is Associated with Response to Abatacept in Rheumatoid Arthritis Patients

Abatacept (CTLA4-Ig)-a monoclonal antibody which restricts T cell activation-is an effective treatment for rheumatoid arthritis (RA). Nevertheless, only 50% of RA patients attain clinical responses, while predictors of response are rather limited. Herein, we aimed to investigate for early biomarkers of response to abatacept, based on a detailed immunological profiling of peripheral blood (PB) cells and serum proteins. We applied flow cytometry and proteomics analysis on PB immune cells and serum respectively, of RA patients starting abatacept as the first biologic agent. After 6 months of treatment, 34.5% of patients attained response. At baseline, Th1 and FoxP3+ T cell populations were positively correlated with tender joint counts (p-value = 0.047 and p-value = 0.022, respectively). Upon treatment, CTLA4-Ig effectively reduced the percentages of Th1 and Th17 only in responders (p-value = 0.0277 and p-value = 0.0042, respectively). Notably, baseline levels of Th1 and myeloid cell populations were significantly increased in PB of responders compared to non-responders (p-value = 0.009 and p-value = 0.03, respectively). Proteomics analysis revealed that several inflammatory mediators were present in serum of responders before therapy initiation and strikingly 10 amongst 303 serum proteins were associated with clinical responses. Finally, a composite index based on selected baseline cellular and proteomics' analysis could predict response to abatacept with a high sensitivity (90%) and specificity (88.24%).

AT2 cell-derived IgA trapped by the extracellular matrix in silica-induced pulmonary fibrosis

Pulmonary fibrosis is an interstitial lung disease caused by various factors such as exposure to workplace environmental contaminants, drugs, or X-rays. Epithelial cells are among the driving factors of pulmonary fibrosis. Immunoglobulin A (IgA), traditionally thought to be secreted by B cells, is an important immune factor involved in respiratory mucosal immunity. In the current study, we found that lung epithelial cells are involved in IgA secretion, which, in turn, promotes pulmonary fibrosis. Spatial transcriptomics and single-cell sequencing suggest that Igha transcripts were highly expressed in the fibrotic lesion areas of lungs from silica-treated mice. Reconstruction of B-cell receptor (BCR) sequences revealed a new cluster of AT2-like epithelial cells with a shared BCR and high expression of genes related to IgA production. Furthermore, the secretion of IgA by AT2-like cells was trapped by the extracellular matrix and aggravated pulmonary fibrosis by activating fibroblasts. Targeted blockade of IgA secretion by pulmonary epithelial cells may be a potential strategy for treating pulmonary fibrosis.

ProtoCell4P: an explainable prototype-based neural network for patient classification using single-cell RNA-seq

MOTIVATION

The rapid advance in single-cell RNA sequencing (scRNA-seq) technology over the past decade has provided a rich resource of gene expression profiles of single cells measured on patients, facilitating the study of many biological questions at the single-cell level. One intriguing research is to study the single cells which play critical roles in the phenotypes of patients, which has the potential to identify those cells and genes driving the disease phenotypes. To this end, deep learning models are expected to well encode the single-cell information and achieve precise prediction of patients' phenotypes using scRNA-seq data. However, we are facing critical challenges in designing deep learning models for classifying patient samples due to (i) the samples collected in the same dataset contain a variable number of cells-some samples might only have hundreds of cells sequenced while others could have thousands of cells, and (ii) the number of samples available is typically small and the expression profile of each cell is noisy and extremely high-dimensional. Moreover, the black-box nature of existing deep learning models makes it difficult for the researchers to interpret the models and extract useful knowledge from them.

RESULTS

We propose a prototype-based and cell-informed model for patient phenotype classification, termed ProtoCell4P, that can alleviate problems of the sample scarcity and the diverse number of cells by leveraging the cell knowledge with representatives of cells (called prototypes), and precisely classify the patients by adaptively incorporating information from different cells. Moreover, this classification process can be explicitly interpreted by identifying the key cells for decision making and by further summarizing the knowledge of cell types to unravel the biological nature of the classification. Our approach is explainable at the single-cell resolution which can identify the key cells in each patient's classification. The experimental results demonstrate that our proposed method can effectively deal with patient classifications using single-cell data and outperforms the existing approaches. Furthermore, our approach is able to uncover the association between cell types and biological classes of interest from a data-driven perspective.

AVAILABILITY AND IMPLEMENTATION

https://github.com/Teddy-XiongGZ/ProtoCell4P.

Advanced methods and novel biomarkers in autoimmune diseases ‑ a review of the recent years progress in systemic lupus erythematosus

There are several autoimmune and rheumatic diseases affecting different organs of the human body. Multiple sclerosis (MS) mainly affects brain, rheumatoid arthritis (RA) mainly affects joints, Type 1 diabetes (T1D) mainly affects pancreas, Sjogren's syndrome (SS) mainly affects salivary glands, while systemic lupus erythematosus (SLE) affects almost every organ of the body. Autoimmune diseases are characterized by production of autoantibodies, activation of immune cells, increased expression of pro-inflammatory cytokines, and activation of type I interferons. Despite improvements in treatments and diagnostic tools, the time it takes for the patients to be diagnosed is too long, and the main treatment for these diseases is still non-specific anti-inflammatory drugs. Thus, there is an urgent need for better biomarkers, as well as tailored, personalized treatment. This review focus on SLE and the organs affected in this disease. We have used the results from various rheumatic and autoimmune diseases and the organs involved with an aim to identify advanced methods and possible biomarkers to be utilized in the diagnosis of SLE, disease monitoring, and response to treatment.

Dysregulation of Immune Cell Subpopulations in Atypical Hemolytic Uremic Syndrome

Atypical hemolytic uremic syndrome (aHUS) is a rare, life-threatening thrombotic microangiopathy. Definitive biomarkers for disease diagnosis and activity remain elusive, making the exploration of molecular markers paramount. We conducted single-cell sequencing on peripheral blood mononuclear cells from 13 aHUS patients, 3 unaffected family members of aHUS patients, and 4 healthy controls. We identified 32 distinct subpopulations encompassing 5 B-cell types, 16 T- and natural killer (NK) cell types, 7 monocyte types, and 4 other cell types. Notably, we observed a significant increase in intermediate monocytes in unstable aHUS patients. Subclustering analysis revealed seven elevated expression genes, including NEAT1, MT-ATP6, MT-CYB, VIM, ACTG1, RPL13, and KLRB1, in unstable aHUS patients, and four heightened expression genes, including RPS27, RPS4X, RPL23, and GZMH genes, in stable aHUS patients. Additionally, an increase in the expression of mitochondria-related genes suggested a potential influence of cell metabolism on the clinical progression of the disease. Pseudotime trajectory analysis revealed a unique immune cell differentiation pattern, while cell-cell interaction profiling highlighted distinctive signaling pathways among patients, family members, and controls. This single-cell sequencing study is the first to confirm immune cell dysregulation in aHUS pathogenesis, offering valuable insights into molecular mechanisms and potential new diagnostic and disease activity markers.

Causal association between systemic lupus erythematosus and the risk of dementia: A Mendelian randomization study

Introduction

It is well-documented that systemic lupus erythematosus (SLE) is associated with dementia. However, the genetic causality of this association remains unclear. Mendelian randomization (MR) was used to investigate the potential causal relationship between SLE and dementia risk in the current study.

Methods

We selected 45 single nucleotide polymorphisms (SNPs) associated with SLE from publicly available genome-wide association studies (GWAS). Summary level statistics were obtained from the dementia GWAS database. MR estimates were performed using the inverse variance weighted (IVW) method, MR-Egger method and weighted median (WM) method. Cochran's Q test, the intercept of MR-Egger, MR-Pleiotropy Residual Sum and Outlier method, leave-one-out analysis and funnel plot were applied for sensitivity analyses.

Results

No significant causal association was found between SLE and any type of dementia, including Alzheimer's disease, vascular dementia, frontotemporal dementia, and dementia with Lewy bodies. These findings were robust across several sensitivity analyses.

Conclusion

Overall, our findings do not support a causal association between SLE and dementia risk.