ReviewEXCLI journal2025
Endocrine polyautoimmunity: Mechanistic insights and the future of AI-driven diagnostics.
Review in EXCLI journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- From genes to environment: A life-course approach to prevent pediatric autoimmune diseases.World journal of clinical pediatrics · 2026Review
- Using HLA-DR3-CBA/J Humanized Mice to Develop a Novel Genetic Model for Autoimmune Thyroiditis.Genes · 2026Article
- Autoimmune gastritis: a comprehensive review of pathophysiology, risk stratification, and management.Frontiers in immunology · 2026Review
- Stress-driven remodeling of antigen presentation and chemokine signaling in pancreatic β-cells: implications for type 1 diabetes.Frontiers in immunology · 2026Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The most prevalent form of polyautoimmunity is autoimmune thyroid diseases (AITD), which frequently coexist with other autoimmune disorders and often act as a central conductor in the symphony of autoimmunity. Due to overlapping clinical manifestations, diagnosing polyautoimmunity presents significant clinical challenges. Patients with AITD exhibit increased susceptibility to additional autoimmune disorders, in which the exact etiology and underlying mechanisms of these associations remain incompletely understood. In this review, we aim to discuss how mechanistic insights contribute to our understanding of the associations between endocrine autoimmune diseases to recognize shared immunological, genetical, and pathological patterns for these diseases. Recent findings, including epitope spreading, cytokine imbalance, shared thyroidal and non-thyroidal autoantibodies, and common genetic susceptibilities, are highlighted. Additionally, the integration of artificial intelligence (AI) into autoimmune diagnostics is addressed, underscoring AI's potential to enhance early detection, improve diagnostic accuracy, and support personalized treatment approaches. By recognizing distinct immunological, genetical and pathological patterns within polyautoimmunity, clinicians and researchers can more effectively target the root causes of immune dysregulation, enabling improved management through personalized strategies and advanced AI-driven tools. See also the graphical abstract(Fig. 1).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.