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Multi-omics integration in autoimmune encephalitis: from novel biomarker discovery to precision therapeutic strategies

Jul 2026 · Frontiers in Immunology · Vol 17 · 0 citations · 51 references
Medicine

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.

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