Challenges and future directions of AIRR-seq-based diagnostics
Ulrik Stervbo, Paraskevas Filippidis, Felix J. Breden, Lindsay Grey Cowell, Frédéric Davi, Victor Greiff, Anton W. Langerak, Eline T. Luning Prak 等 11 位
University Hospitals of the Ruhr-University of Bochum Humboldt-Universität zu Berlin Universitätsklinik Marien Hospital Herne Charité - Universitätsmedizin Berlin
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摘要与影响
Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a promising diagnostic method across various clinical conditions, yet its widespread implementation faces several challenges. This perspective examines the current landscape of AIRR-seq diagnostics and outlines key obstacles and opportunities for advancement. Critical challenges include the need for standardized quality controls, privacy protection under General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) frameworks, and the development of clinically compatible bioinformatics pipelines. Machine learning approaches offer potential solutions for interpreting complex repertoire signatures, though these models must balance accuracy with interpretability for clinical adoption. Future applications may include early disease detection, prognosis, and monitoring of treatment and vaccine responses. However, successful clinical integration will require sustained collaboration among funding bodies, regulatory agencies, researchers, diagnosticians, and clinicians to establish clear guidelines and expand existing repositories with well-characterized patient samples. The collaborative efforts of the AIRR Diagnostics Working Group and the AIRR Community's initiatives are working towards unlocking the potential of AIRR-seq in precision medicine and enhancing diagnostic capabilities.
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