International stroke genetics consortium recommendations for studies of genetics of stroke outcome and recovery

Well, what you are recommending is a stroke strategy which will never occur until we get survivors in charge.  The existing process has been failing for decades which is why survivors don't recover. 

 International stroke genetics consortium recommendations for studies of genetics of stroke outcome and recovery

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Arne G Lindgren, Robynne G Braun, Jennifer Juhl Majersik, ...

First Published April 26, 2021 Case Report Find in PubMed 

https://doi.org/10.1177/17474930211007288

Article information

Abstract

Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable for multicenter genetic studies of ischemic stroke brain injury and recovery. Our recommendations have been endorsed by the International Stroke Genetics Consortium.

Keywords Data collection, genetics, ischemic stroke, outcome, phenotype, recovery, standardization

Introduction

Genetic studies can potentially discover biological mechanisms affecting stroke recovery with treatment implications. However, they need large sample sizes only achievable by combining data from multiple studies, where harmonized terminology, methodology, and data collection timelines are essential.

The terms stroke outcome and stroke recovery differ in meaning. Stroke outcome describes the degree of function at specific time points; stroke recovery encompasses the degree of improvement (or deterioration) over time and better captures dynamic biological processes. Stroke recovery evaluation requires initial stroke severity data, without which only stroke outcome is measurable. It is also important to distinguish restitution (“true”) recovery from behavioral compensation. For example, “true” motor recovery suggests restoration of pre-stroke movement patterns¹ whereas “compensation,” implies new (possibly dysfunctional) movement patterns for accomplishing functional tasks.²

The dynamics of stroke recovery depend on intrinsic and extrinsic factors.³ Each patient’s recovery pattern uniquely reflects the combined influences of lesion size and location, biological mechanisms of brain repair, comorbidities, pre-morbid health status, and post-stroke factors including acute recanalization, rehabilitation, psychosocial factors, and environmental influences. Consequently, the degree of stroke recovery varies considerably between individuals, and even skilled clinicians have difficulty making accurate recovery predictions.⁴

The need for improved predictive models of stroke recovery has become a major research focus^5,6 and recent studies suggest that genetic variations influence recovery after stroke.^7–9 Despite multiple studies, findings remain heterogeneous, due to differences in populations, recovery metrics, assessment time points, and study designs. Most studies using global assessments incorporate the modified Rankin Scale (mRS)¹⁰ while some use more detailed modality-specific functions, for example, upper extremity (UE) motor function, language or cognitive function,^3,11 or patient-reported outcome measures (PROMs). Few studies use repeated measures, leading to knowledge gaps on stroke recovery time course. To standardize timing and metric choices across studies, the Stroke Recovery and Rehabilitation Roundtable taskforce in 2017 recommended core outcomes for trials and standardized measurement time points to reduce heterogeneity.¹¹

Here, we focus specifically on design of prospective genetic studies of ischemic stroke (IS) recovery, aiming to ascertain the underlying genetic influences on stroke recovery biology. Our recommendations complement existing advise for standardizing phenotype data¹² and biological sample collection¹³ for stroke risk and recovery studies^11,14 by providing recommendations for pre-specified harmonized data sets suitable for large, high-quality, multi-center collaborations in prospective stroke genetic recovery studies. We propose measures comprehensive enough to provide both stroke- and domain-specific data, but simple enough to allow collection of large sample sizes across numerous and diverse enrollment sites. This will allow opportunities to discover genetic factors influencing hitherto unknown biological pathways affecting the dynamics of IS recovery. We do not here consider intracerebral hemorrhage (ICH) given ICH recovery mechanisms differ from IS.

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