TY - CHAP
T1 - Multi-Omics Approaches to Discovering Acute Stroke Injury and Recovery Mechanisms
AU - Giles, James
AU - Lee, Jin Moo
AU - Dhar, Rajat
N1 - Publisher Copyright:
© Mayo Clinic, The Editor(s) and The Author(s), under exclusive licence to Springer International Publishing AG, part of Springer Nature 2024.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - Millions of people suffer an acute stroke each year, resulting in an enormous global burden of residual disability and mortality. Despite decades of work to discover effective therapeutics to prevent the consequences of ischemic injury and promote recovery, there have been hundreds of failed clinical trials. Genetics and other omics offer the opportunity to apply ‘reverse translational’ approaches to discover mechanisms important to mitigating injury and promoting recovery. In this chapter, we present a rationale and outline methodology for this broad investigative approach, including the development of creative endophenotypes and integration of multi-omic bioinformatics, as means of enhancing the discovery pathway. We also discuss the urgent need to expand collaborations and harness emerging technologies such as artificial intelligence to phenotype large enough cohorts to have adequate power to find genes and pathways relevant to stroke outcomes. Finally, we discuss challenges and future directions in this rapidly expanding area of stroke research.
AB - Millions of people suffer an acute stroke each year, resulting in an enormous global burden of residual disability and mortality. Despite decades of work to discover effective therapeutics to prevent the consequences of ischemic injury and promote recovery, there have been hundreds of failed clinical trials. Genetics and other omics offer the opportunity to apply ‘reverse translational’ approaches to discover mechanisms important to mitigating injury and promoting recovery. In this chapter, we present a rationale and outline methodology for this broad investigative approach, including the development of creative endophenotypes and integration of multi-omic bioinformatics, as means of enhancing the discovery pathway. We also discuss the urgent need to expand collaborations and harness emerging technologies such as artificial intelligence to phenotype large enough cohorts to have adequate power to find genes and pathways relevant to stroke outcomes. Finally, we discuss challenges and future directions in this rapidly expanding area of stroke research.
UR - http://www.scopus.com/inward/record.url?scp=85205660181&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-41777-1_19
DO - 10.1007/978-3-031-41777-1_19
M3 - Chapter
AN - SCOPUS:85205660181
SN - 9783031417764
SP - 547
EP - 584
BT - Stroke Genetics, Third Edition
PB - Springer International Publishing
ER -