Beta Cell Autoantibody Profiles in Type 1 Diabetes: Predictive Biomarkers for Progression
Nakawungu Catherine
Department of Pharmaceutical Microbiology and Biotechnology Kampala International University Uganda
Email: catherine.nakawungu@studwc.kiu.ac.ug
ABSTRACT
Type 1 diabetes represents a complex autoimmune disorder characterized by progressive beta cell destruction, affecting approximately 1.1 million children and adolescents globally with an increasing incidence of 3-4% annually. Beta cell autoantibodies served as critical biomarkers for disease prediction and progression monitoring, providing insights into autoimmune processes preceding clinical onset. This review synthesized current evidence on autoantibody profiles as predictive biomarkers for type 1 diabetes progression. A comprehensive literature search was conducted using PubMed, EMBASE, and Cochrane databases from 2012 to 2025, focusing on studies evaluating autoantibody characteristics, progression patterns, and predictive algorithms. Current evidence demonstrates that glutamic acid decarboxylase antibodies (GADA), insulinoma antigen-2 antibodies (IA-2A), zinc transporter 8 antibodies (ZnT8A), and insulin autoantibodies (IAA) exhibit distinct predictive capabilities. Multiple autoantibody positivity significantly increased progression risk, with 5-year progression rates exceeding 80% in individuals positive for three or more antibodies. Autoantibody affinity, epitope recognition patterns, and temporal dynamics provided additional prognostic information beyond simple presence or absence. Novel approaches incorporating autoantibody kinetics, metabolomic profiles, and machine learning algorithms enhance predictive accuracy. The integration of comprehensive autoantibody profiling into clinical practice enabled risk stratification, family counseling, and selection of candidates for prevention trials. Clinicians should implement standardized autoantibody screening protocols for high-risk individuals to facilitate early intervention and optimize disease management strategies.
Keywords: Beta cell autoantibodies, Type 1 diabetes, Predictive biomarkers, Autoimmune progression, Disease staging.
CITE AS: Nakawungu Catherine (2025). Beta Cell Autoantibody Profiles in Type 1 Diabetes: Predictive Biomarkers for Progression. IDOSR JOURNAL OF APPLIED SCIENCES 10(2):10-15, 2025. https://doi.org/10.59298/IDOSRJAS/2025/102.1015