Putting the "mi" in omics: discovering miRNA biomarkers for pediatric precision care.
Putting the "mi" in omics: discovering miRNA biomarkers for pediatric precision care.
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DOI：
10.1038/s41390-022-02206-5
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发表时间：
2023-01
影响因子：
3.6
通讯作者：
Hicks, Steven D.
中科院分区：
文献类型：
--
作者：
Li, Chengyin;Sullivan, Rhea E.;Zhu, Dongxiao;Hicks, Steven D.
在过去的十年里，人们对微小核糖核酸(MiRNAs)的兴趣与日俱增，将这些非编码的小核酸推向了生物标记物研究的前沿。科学知识的进步已经清楚地表明，miRNAs在调节整个人体的细胞生理方面发挥着至关重要的作用。MiRNA信号的扰动也被描述在各种儿科疾病中--从癌症到肾功能衰竭，再到创伤性脑损伤。同样，将患者miRNA组学与纵向临床数据配对的跨儿科学科的研究数量也在增加。分析这些庞大的多变量数据集需要了解儿科表型数据、数据科学和基因组学。使用机器学习技术来辅助生物标记物检测，有助于破译数据中具有生物学意义的变化中的背景噪声。此外，新出现的研究表明，miRNAs可能有潜力作为儿科精确护理的治疗靶点。在这里，我们回顾了目前儿科疾病的miRNA生物标记物，以及结合机器学习技术、miRNA组学和患者健康数据的研究，以确定新的儿科疾病生物标记物和潜在的治疗方法。
In the past decade, growing interest in microribonucleic acids (miRNAs) has catapulted these small, non-coding nucleic acids to the forefront of biomarker research. Advances in scientific knowledge have made it clear that miRNAs play a vital role in regulating cellular physiology throughout the human body. Perturbations in miRNA signaling have also been described in a variety of pediatric conditions – from cancer, to renal failure, to traumatic brain injury. Likewise, the number of studies across pediatric disciplines that pair patient miRNA-omics with longitudinal clinical data are growing. Analysis of these voluminous, multivariate data sets require understanding of pediatric phenotypic data, data science, and genomics. Use of machine learning techniques to aid in biomarker detection have helped decipher background noise from biologically meaningful changes in the data. Further, emerging research suggests that miRNAs may have potential as therapeutic targets for pediatric precision care. Here, we review current miRNA biomarkers of pediatric diseases and studies that have combined machine learning techniques, miRNA-omics, and patient health data to identify novel biomarkers and potential therapeutics for pediatric diseases.
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