The integration of multi-omics data offers a promising conceptual lens through which to understand the intricate immune-neuronal interactions driving AE, though substantial challenges in data standardization, clinical validation, and implementation remain to be addressed.
Abstract
Autoimmune encephalitis (AE) represents a heterogeneous group of disorders characterized by immune-mediated attacks on neuronal antigens within the central nervous system (CNS), leading to diverse clinical manifestations and posing significant challenges in diagnosis and treatment. Recent advances in multi-omics technologies—including genomics, transcriptomics, proteomics, metabolomics, and immunomics—are beginning to provide unprecedented opportunities to unravel the complex immunopathophysiology of AE at a systems level. This review critically examines the application of integrated multi-omics approaches in AE research, with particular emphasis on immunological mechanisms underlying disease pathogenesis. We focus on: (i) the identification of potential diagnostic and prognostic biomarkers with rigorous validation frameworks; (ii) the elucidation of molecular heterogeneity underlying clinical variability, including B-cell clonal expansion, small-cohort evidence for T follicular helper (Tfh) expansion with inferred T follicular regulatory (Tfr) imbalance, and cytotoxic CD8+ T-cell-mediated neuronal injury in paraneoplastic/intracellular-antigen contexts; (iii) the conceptual development of precision medicine strategies tailored to individual immunophenotypic profiles; and (iv) the critical appraisal of current evidence quality and methodological limitations. By synthesizing current findings, this article aims to establish a comprehensive immunological framework that supports the future advancement of personalized therapeutic interventions. The integration of multi-omics data offers a promising conceptual lens through which to understand the intricate immune-neuronal interactions driving AE, though substantial challenges in data standardization, clinical validation, and implementation remain to be addressed.
Current evidence on advances in clinical research and immunotherapy across the major autoimmune CNS disease groups is synthesized, with a particular focus on trial designs, endpoints, and the evolution from observational cohorts to randomized controlled trials.
Autoimmune diseases (AIDs) like multiple sclerosis (MS), systemic lupus erythematosus (SLE) and inflammatory bowel disease (IBD) share common etiologies and are characterized by dysregulation of the immune system. Nonetheless, they are highly heterogenous disorders that are caused by distinct underlying mechanisms—termed endotypes. AID endotypes—each associated with genetic predisposition, treatment response, and altered molecular pathways—are emerging as clinical phenotypes. Endotype-driven diagnosis, prognosis and treatment rely on biomarkers to select the optimal therapeutic intervention.
In this study, we interrogated human plasma samples from AID patients (i.e., MS, SLE, and IBD) and age- and sex-matched healthy controls for biomarker signatures using multiple platforms. We assessed multiple serum protein using a Meso Scale Discovery (MSD)® platform, a high-sensitivity Quanterix® platform as well as O-Link® technology based on proximity extension. In addition, we employed unbiased mass spectrometry to evaluate the lipidome and the metabolome of the samples. Eventually, we integrated the obtained experimental data with available clinical metadata using DIABLO and analyzed the dataset to extract key predictive features with multiple regularization approaches such as elastic net.
We demonstrated the establishment of a workflow for end-to-end data generation, from human sample acquisition to biomarker discovery and potential patient stratification, including an in-silico framework for data integration and analysis. In addition, we identified three inflammatory clusters among the analyzed patient samples indicating the underlying AID endotypes. Moreover, we found analytes that have significant discrimination power for biomarker discovery.
Multimodal characterization and analysis enable identification of relevant disease endotypes and clinically relevant biomarkers to support patient stratification for clinical studies.
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Translational and Interventional Immunology (TI)
Dennis Özcelik, Julian J Albers, Stéphanie Delmas et al.· Journal of Immunology· 0 citations
This review synthesizes advances in neuroimmunology, clinical phenotyping, diagnostics, immunomodulatory and antiseizure therapies, neuromodulation, and patient and family centered outcomes, and outlines future directions focused on biomarker-driven precision medicine, disease-modifying strategies, and interdisciplinary care models.
Alica M. Goldman, Nora Wong, A. Vezzani et al.· Epilepsy Currents· 0 citations
Introduction. Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system (CNS) characterised by neuroinflammation and neurodegeneration leading to progressive disability. Its complex immunopathogenesis involves autoreactive T cells, B cells, and myeloid cells, with growing evidence highlighting the pivotal role of B lymphocytes. B cells contribute through antigen presentation, cytokine secretion, autoantibody production, and formation of ectopic lymphoid structures, making them key therapeutic targets. Current disease-modifying therapies (DMTs), including anti-CD20 monoclonal antibodies such as ocrelizumab, ofatumumab, and recently launched ublituximab, have significantly improved clinical outcomes. However, optimisation of long-term efficacy and safety remains challenging. The novel agent, frexalimab, which targets the CD40–CD40L pathway, aims to refine treatment precision and safety further.Material and methods. A systematic search of PubMed, Scopus, and Web of Science (October–November 2025) was conducted to identify clinical trials and high-quality reviews on emerging MS therapies, with emphasis on anti-CD20 agents, BTK inhibitors, frexalimab, and CAR-T therapy. Eligible studies were critically appraised for mechanisms of action, clinical efficacy, safety, and relevance, with particular focus on recent phase II–III data.Results. This review synthesises current insights into MS immunopathology and recent advances in B-cell-targeted therapies and CAR-T approaches, highlighting an evolving therapeutic landscape focused on improving disease control and long-term outcomes.Conclusions. Continued development of targeted immunotherapies may bring the field closer to sustained remission, effective prevention of progression, and potentially enhanced CNS repair.
Julia Lewtak, Kamil Syga, A. Jamróz-Wiśniewska et al.· Journal of Medical Sciences· 0 citations
Uveitis encompasses a group of intraocular inflammatory disorders that notably contribute to global visual morbidity. Persistent challenges include early diagnosis, accurate subtype classification and individualized treatment. Recent advances in omics technologies, including genomics, epigenetics, transcriptomics, single-cell omics, proteomics, metabolomics, lipidomics and microbiome profiling, have reshaped the current understanding of uveitis pathogenesis by uncovering disease-associated genetic variants, dynamic transcriptional landscapes, inflammatory proteins, metabolic alterations, and microbe-host interactions. Notably, single-cell RNA sequencing offers unprecedented insights into retinal immune cell heterogeneity and functional states, while radiomics is emerging as a valuable platform for imaging biomarkers. The present review summarizes key findings from multi-omics studies in uveitis, described the sample sources and analytical strategies employed, and highlighted the transformative potential of integrative omics in precision ophthalmology. Multi-omics approaches hold promise for identifying novel biomarkers and therapeutic targets, refining disease classification, and enabling tailored interventions for patients with uveitis.
Chengzhi Liu, Qiong Wu, M. Yuan et al.· International Journal of Mol...· 0 citations
Systemic lupus erythematosus (SLE) is a complex autoimmune disorder characterized by multi-organ involvement and a protracted clinical course. Current diagnostic strategies, which rely heavily on clinical symptoms and serology, are often insufficient for early detection. Therefore, highly accurate diagnostic biomarkers are urgently needed to facilitate early intervention and optimize personalized treatment strategies. D atasets GSE61635 and GSE135779 were integrated to identify differentially expressed genes. Weighted gene co-expression network analysis (WGCNA) was performed to isolate the module with the strongest clinical relevance. Mendelian randomization and single‑cell RNA‑seq were used to identify key disease‑relevant genes. A diagnostic model was then constructed, and gene set variation analysis (GSVA), along with gene set enrichment analysis (GSEA), was conducted to elucidate the underlying molecular pathways.
IFIT1
and
IFIT3
were identified as 2 core genes highly expressed in monocytes and T cells of SLE patients. Functional enrichment analysis revealed that these genes were enriched in immune-related pathways, metabolic pathways related to inflammation and genomic stability. The diagnostic model showed good accuracy, with an area under the curve (AUC) of 0.974 on the training set and 0.912 on the validation set.
IFIT1
and
IFIT3
represent promising biomarkers for diagnosing SLE and appear to mediate key immune and metabolic disturbances. Furthermore, the developed model serves as an accurate and reliable instrument for early diagnosis and personalized therapy. Large-scale clinical studies are warranted to further validate these findings and evaluate their clinical application.
Luofei Huang, Jian Shi· Clinical and Experimental Me...· 0 citations