摘要
多组学技术、队列研究设计、数据科学和机器学习的进步已经开始改变循证医学,为下一代"深度"医学的未来提供了诱人的前景.总结了基因组与基因组修饰测序、转录组与单细胞转录组、蛋白组、代谢组、微生物组、影像组与生物传感器等多组学实验技术和全基因组关联分析、全基因组关联信号解读、多基因风险评分、孟德尔随机化与人工智能算法等大数据分析技术的发展趋势,探讨了这些技术在疾病分型、诊断与预测、药物研发和临床试验设计等方面的临床应用.针对多组学大数据与医学发展面临的挑战,展望了未来队列设计、数据管理与共享、国际合作等发展方向.
Abstract
Advances in multi-omics technologies,cohort study design,data science,and machine learning are transforming evidence-based medicine,offering a promising outlook for the future of next-generation"deep"medicine.We hereby summarized the development trends in multi-omics experimental techniques,including genomics and epigenomics sequencing,transcriptomics and single-cell transcriptomics,proteomics,metabolomics,microbiomics,imaging,and biosensors.Furthermore,we introduced progress in big data analysis methods such as genome-wide association studies,interpretation of genome-wide association signals,polygenic risk scoring,Mendelian randomization,and artificial intelligence algorithms.Additionally,we discussed the clinical applications of these technologies in disease subtyping,diagnosis and prediction,drug development,and clinical trial design.Finally,we discussed the challenges faced and explored future directions in cohort study design,data management and sharing,and the enhancement of international collaboration.
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