Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

被引:7
作者
Scarpa, Joseph R. [1 ]
Elemento, Olivier [2 ]
机构
[1] Weill Cornell Med, Dept Anesthesiol, New York, NY 10065 USA
[2] Cornell Univ, Caryl & Israel Englander Inst Precis Med, Weill Cornell Med, New York, NY USA
关键词
artificial intelligence; genomics; machine learning; network biology; perioperative outcome; precision medi-cine; transcriptomics; CORONARY-ARTERY-DISEASE; GENE-EXPRESSION; MALIGNANT HYPERTHERMIA; TRANSCRIPTIONAL SIGNATURES; INTRAOPERATIVE OPIOIDS; FAMILIAL AGGREGATION; ATRIAL-FIBRILLATION; SYSTEMS GENETICS; IMMUNE-RESPONSE; RISK PREDICTION;
D O I
10.1016/j.bja.2023.03.006
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules -the 'multi-omic' profile -can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clini-cally similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repur-posed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.
引用
收藏
页码:26 / 36
页数:11
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