title: Principles of precision medicine in stroke.
abstract: The era of precision medicine has arrived and conveys tremendous potential, particularly for stroke neurology. The diagnosis of stroke, its underlying aetiology, theranostic strategies, recurrence risk and path to recovery are populated by a series of highly individualised questions. Moreover, the phenotypic complexity of a clinical diagnosis of stroke makes a simple genetic risk assessment only partially informative on an individual basis. The guiding principles of precision medicine in stroke underscore the need to identify, value, organise and analyse the multitude of variables obtained from each individual to generate a precise approach to optimise cerebrovascular health. Existing data may be leveraged with novel technologies, informatics and practical clinical paradigms to apply these principles in stroke and realise the promise of precision medicine. Importantly, precision medicine in stroke will only be realised once efforts to collect, value and synthesise the wealth of data collected in clinical trials and routine care starts. Stroke theranostics, the ultimate vision of synchronising tailored therapeutic strategies based on specific diagnostic data, demand cerebrovascular expertise on big data approaches to clinically relevant paradigms. This review considers such challenges and delineates the principles on a roadmap for rational application of precision medicine to stroke and cerebrovascular health.
authors.affiliation: Department of Neurology, Neurovascular Imaging Research Core and the UCLA Stroke Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
authors.forename: Jason D
authors.initials: JD
authors.lastname: Hinman
authors.affiliation: Department of Neurology, Philip Kistler Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Natalia S
authors.initials: NS
authors.lastname: Rost
authors.affiliation: Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong.
authors.forename: Thomas W
authors.initials: TW
authors.lastname: Leung
authors.affiliation: Neurovascular Research Laboratory, Vall d'Hebron Research Institute (VHIR), Barcelona & IBIS Stroke Programme, Hospital Virgen Macarena-Rocio, Sevilla, Spain.
authors.forename: Joan
authors.initials: J
authors.lastname: Montaner
authors.affiliation: Institute of Neuroscience & Psychology, Glasgow, UK.
authors.forename: Keith W
authors.initials: KW
authors.lastname: Muir
authors.affiliation: Altair Biostatistics, St. Louis Park, Minnesota, USA.
authors.forename: Scott
authors.initials: S
authors.lastname: Brown
authors.affiliation: Stroke Unit, Department of Neurology and Medicine, Hospital Clínico Universitario, Universidad de Valladolid, Valladolid, Spain.
authors.forename: Juan F
authors.initials: JF
authors.lastname: Arenillas
authors.affiliation: Baystate Medical Center, Springfield, Massachusetts, USA.
authors.forename: Edward
authors.initials: E
authors.lastname: Feldmann
authors.affiliation: Department of Neurology, Neurovascular Imaging Research Core and the UCLA Stroke Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
authors.forename: David S
authors.initials: DS
authors.lastname: Liebeskind
mesh_terms: D006801:Humans; D057285:Precision Medicine; D020521:Stroke
keywords: CEREBRAL BLOOD FLOW; CEREBROVASCULAR; IMAGE ANALYSIS; NEUROGENETICS; STATISTICS