Dimitri Paul
Department of Paediatric Endocrinology, Sheffield Children's NHS Foundation Trust, Sheffield, UK.
The College of Health, Wellbeing and Life Sciences, Sheffield Hallam University, Sheffield, UK.
Camb Prism Precis Med. 2023 Feb 3;1:e17. doi: 10.1017/pcm.2023.4. eCollection 2023.
Medical practice is transforming from a reactive to a pro-active and preventive discipline that is underpinned by precision medicine. The advances in technologies in such fields as genomics, proteomics, metabolomics, transcriptomics and artificial intelligence have resulted in a paradigm shift in our understanding of specific diseases in childhood, greatly enhanced by our ability to combine data from changes within cells to the impact of environmental and population changes. Diseases in children have been reclassified as we understand more about their genomic origin and their evolution. Genomic discoveries, additional 'omics' data and advances such as optical genome mapping have driven rapid improvements in the precision and speed of diagnoses of diseases in children and are now being incorporated into newborn screening, have improved targeted therapies in childhood and have supported the development of predictive biomarkers to assess therapeutic impact and determine prognosis in congenital and acquired diseases of childhood. New medical device technologies are facilitating data capture at a population level to support higher diagnostic accuracy and tailored therapies in children according to predicted population outcome, and digital ecosystems now tailor therapies and provide support for their specific needs. By capturing biological and environmental data as early as possible in childhood, we can understand factors that predict disease or maintain health and track changes across a more extensive longitudinal path. Data from multiple health and external sources over long-time periods starting from birth or even in the environment will provide further clarity about how to sustain health and prevent or predict disease. In this respect, we will not only use data to diagnose disease, but precision diagnostics will aid the 'diagnosis of good health'. The principle of 'start early and change more' will thus underpin the value of applying a personalised medicine approach early in life.
医学实践正在从一种被动反应式的学科转变为以精准医学为支撑的主动预防学科。基因组学、蛋白质组学、代谢组学、转录组学和人工智能等领域的技术进步,导致我们对儿童特定疾病的理解发生了范式转变,而我们将细胞内变化的数据与环境和人群变化的影响相结合的能力极大地增强了这种转变。随着我们对儿童疾病的基因组起源及其演变有了更多了解,儿童疾病已被重新分类。基因组学发现、额外的“组学”数据以及诸如光学基因组图谱等进展,推动了儿童疾病诊断的精准度和速度迅速提高,目前这些技术已被纳入新生儿筛查,改善了儿童的靶向治疗,并支持开发预测性生物标志物以评估治疗效果并确定儿童先天性和后天性疾病的预后。新的医疗设备技术正在促进在人群层面的数据采集,以支持更高的诊断准确性,并根据预测的人群结果为儿童提供个性化治疗,而数字生态系统现在可以定制治疗方案并满足他们的特定需求。通过在儿童时期尽早收集生物和环境数据,我们可以了解预测疾病或维持健康的因素,并在更广泛的纵向过程中跟踪变化。从出生甚至在胎儿期开始的长期内来自多个健康和外部来源的数据,将进一步明确如何维持健康以及预防或预测疾病。在这方面,我们不仅将使用数据来诊断疾病,而且精准诊断将有助于“健康诊断”。因此,“尽早开始并做出更多改变”的原则将支撑在生命早期应用个性化医疗方法的价值。