"FZK 01KX1818"
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Early detection of type 1 diabetes, in its presymptomatic stage, offers significant clinical advantages, including treatment that can delay disease onset. Current screening focuses on identifying islet autoantibody positivity, with proposed optimal testing at ages 2, 6 and 10 years potentially achieving up to 80% sensitivity. However, challenges arise from participation rates and costs associated with multiple screenings. Genetic pre-screening has been suggested as a complementary strategy to target high-risk individuals prior to autoantibody testing, but its real-world benefits remain uncertain. Broad genetic selection strategies, based on family history, HLA typing or polygenic risk scores, can identify subsets of the population at elevated risk. However, these approaches face issues like low recall rates, socioeconomic biases and limited applicability across diverse ancestries. Additionally, the cost-effectiveness and infrastructure requirements of integrating genetic testing into routine healthcare remain significant hurdles. The combined use of genetic and autoantibody testing could improve predictive value, especially with innovations like point-of-care genetic testing. Yet, the ultimate success of any screening programme depends less on specific strategies and more on maximising public and healthcare-provider engagement, ensuring high participation, and addressing socioeconomic and demographic disparities. Digital-health infrastructure may play a crucial role in improving recall rates and maintaining follow-up adherence. In conclusion, while repeated islet autoantibody screening remains the most effective standalone approach, conducting genetic screening prior to islet autoantibody testing may be practical in certain contexts, provided that sufficient resources and equitable strategies are employed. Public engagement and robust infrastructure are essential to realising the full potential of early type 1 diabetes detection programmes.
