Study on stroke informs drug discovery and risk prediction

Stroke is the second leading cause of death worldwide, responsible for approximately 12% of total deaths, and a contributor to years of life lost or lived with disability. The incidence and severity of stroke is high in low- and middle-income countries, where 70% of total stroke deaths occur.

The results of the largest genomic study on stroke were recently published online in the world’s leading multidisciplinary science journal, Nature.

The study was based on DNA samples of more than 2.5 million participants of whom 200,000 had a stroke. Participants were of European, East-Asian, African, South-Asian, and Latin-American ancestry (a third of stroke patients were non-European). They were derived from numerous hospital-based and population-based cohorts and biobanks, as well as five clinical trials. 

The study was conducted by members of the GIGASTROKE consortium, involving several international consortia and networks, such as ISGC and CHARGE, and investigators from over 20 countries, including Professor Jane Maguire, Deputy Head of School (Research) in the School of Nursing and Midwifery at UTS.

“I never thought that my humble Australian stroke dataset, collected from generous stroke survivors in NSW for my PhD, would eventually contribute to knowledge generation at this global level,” said Professor Maguire.

“I am incredibly fortunate to be part of this worldwide effort. My colleagues, the international stroke genetics research community, continue to explore new approaches to stroke prevention and care for all populations, through better informed, targeted stroke management and treatments.”

It was co-led by two research centers at the University of Bordeaux (France) and LMU University in Munich (Germany), together with research departments at the University of Tokyo (Japan), the University of Tartu (Estonia), Ibadan University (Nigeria), the VA Boston Healthcare System and Harvard Medical School (USA). 

I never thought that my humble Australian stroke dataset, collected from generous stroke survivors in NSW for my PhD, would eventually contribute to knowledge generation at this global level.

Professor Jane Maguire
Deputy Head of School (Research)
UTS School of Nursing and Midwifery

The researchers found substantial shared genetic susceptibility to stroke across the different ancestry groups, and the effects of identified genomic regions were mostly of similar magnitude across ancestries. 

Characterized by a neurological deficit of sudden onset, stroke is predominantly caused by an ischemic stroke (where clotting of an artery occurs, and of which the main subtypes are related to atheroma, cardiac disease, and small-vessel disease) and, less often, by an intracerebral hemorrhage due to bleeding in the brain.

Most of the associations observed in this study were with any stroke or any ischemic stroke, while some were specific for ischemic stroke subtypes. 

By combining their results with existing data on gene expression in different tissues or brain cell types and protein levels in the blood, cerebrospinal fluid and brain, the researchers obtained preliminary insights into the specific genes involved and the biological mechanisms through which they may contribute to the occurrence of stroke. 

The researchers also aggregated all genetic risk factors for stroke from different ancestry groups into a polygenic score, which evaluates the effect of thousands of genetic variants, and found the score to be strongly associated with ischemic stroke risk in Europeans and, for the first time, in East Asians.

There were not enough participants to generate an African-specific stroke polygenic score, however the European score showed a significant, although weaker, association with ischemic stroke in African American and indigenous African participants. 

Leveraging data from 5 clinical trials in 52,600 patients, the researchers further showed that, in combination, the identified genetic risk factors for stroke predicted ischemic stroke independently of clinical risk factors (hypertension, smoking, etc.) and much more strongly than in previous work based on smaller genetic datasets.