基于airr -seq的诊断的挑战和未来方向

Ulrik Stervbo , Paraskevas Filippidis , Felix Breden , Lindsay G. Cowell , Frederic Davi , Victor Greiff , Anton W. Langerak , Eline T. Luning Prak , Alexandra F. Sharland , Enkelejda Miho , Pieter Meysman
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引用次数: 0

摘要

适应性免疫受体库测序(AIRR-seq)是一种很有前途的诊断方法,适用于各种临床条件,但其广泛实施面临着一些挑战。这一观点考察了AIRR-seq诊断的现状,并概述了发展的主要障碍和机会。关键的挑战包括需要标准化的质量控制,在通用数据保护条例(GDPR)和健康保险流通与责任法案(HIPAA)框架下的隐私保护,以及开发临床兼容的生物信息学管道。机器学习方法为解释复杂的曲目特征提供了潜在的解决方案,尽管这些模型必须平衡准确性和临床采用的可解释性。未来的应用可能包括早期疾病检测、预后、治疗和疫苗反应监测。然而,成功的临床整合将需要资助机构、监管机构、研究人员、诊断医生和临床医生之间的持续合作,以建立明确的指导方针,并扩大现有的具有良好特征的患者样本库。AIRR诊断工作组和AIRR社区的倡议正在共同努力,以释放AIRR-seq在精准医学和增强诊断能力方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and future directions of AIRR-seq-based diagnostics
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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来源期刊
Immunoinformatics (Amsterdam, Netherlands)
Immunoinformatics (Amsterdam, Netherlands) Immunology, Computer Science Applications
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