Early warning for stroke via genes
Genomic risk score offers predictive value comparable to clinical risk factors for ischemic stroke
MUNICH—One of the big goals in the wake of greater understanding of DNA and ever-better and less expensive ways to sequence and analyze the genome has been to use gene testing as a more accurate diagnostic tool than traditional methods. Researchers at Ludwig-Maximilians-Universität (LMU) in Munich, Germany, say that according to their work, estimates based on genomic data predict stroke risk with an accuracy similar to—or greater than—those based on clinical risk factors.
In collaboration with researchers at University of Cambridge in the United Kingdom and the Baker Heart and Diabetes Institute in Melbourne, Australia, Prof. Martin Dichgans of the LMU Medical Center says that genetic data obtained from a single sample of blood or saliva can identify persons who have a threefold higher risk (than the average for the population as a whole) of suffering an ischemic stroke. And, as already noted, he says that this genetically based estimate of risk is as reliable, or even more so, than that based on the assessment of conventionally recognized clinical risk factors.
The new findings appeared in the online journal Nature Communications under the title “Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke.”
The authors of the study conclude that, based on their results, people with a high genetic risk score may need more meticulous monitoring and more intensive preventive interventions than current guidelines suggest.
As noted by the authors in their paper, “Recent genome-wide association studies in stroke have enabled the generation of genomic risk scores (GRS) but their predictive power has been modest compared to established stroke risk factors. Here, using a meta-scoring approach, we develop a metaGRS for ischaemic stroke (IS) and analyse this score in the UK Biobank (n = 395,393; 3075 IS events by age 75). The metaGRS hazard ratio for IS (1.26, 95% CI 1.22–1.31 per metaGRS standard deviation) doubles that of a previous GRS, identifying a subset of individuals at monogenic levels of risk: the top 0.25% of metaGRS have three-fold risk of IS.”
More importantly, the researchers say, is how much of a head-start genomic risk analysis could offer, noting that “Genomic risk prediction has a notable advantage over established risk factors as it could be used to infer risk of disease from birth, thus allowing the initiation of preventive strategies before conventional risk factors manifest and their discriminative capacity begins to emerge.”
Strokes are the second most common cause of death worldwide, and the leading cause of physical disabilities in adults. Approximately 80 percent of all cases of stroke are the result of ischemia—that is, an acute lack of oxygen owing to the obstruction of blood flow through a cerebral artery in the brain. The individual level of risk for ischemic stroke is determined by a combination of genetic factors and pre-existing disorders, such as high blood pressure and diabetes.
How the researchers came to their conclusions was first to use a machine learning approach to analyze a large body of genetic data obtained by a variety of research groups in genome-wide association studies that identified gene variants which can be correlated with increased risk of stroke. On the basis of this analysis, they assigned an individual genetic risk score to each combination of pre-disposing variants. They then tested the predictive value of these risk scores by comparing them with data from a long-term prospective study, which has collected health-related information, including genomic data, from 420,000 individuals. These data are now archived in the UK Biobank.
The results of their comparative analysis demonstrated that the new genetic estimator of stroke risk is more precise than those employed up to now, and is comparable in reliability to other estimates based on known behavioral or physiological factors such as cigarette smoking or body mass index (BMI). Moreover, the genetic risk score is a significantly more successful predictor of future episodes of ischemic stroke than an evaluation of the medical histories of a subject’s family.
“The sequencing of the human genome has revealed many insights. For common diseases, such as stroke, it is clear that genetics is not destiny; however, each person does have their own innate risk for any particular disease. The challenge is now how we best incorporate this risk information into clinical practice so that the public can live healthier and longer,” said Dr. Michael Inouye of the Baker Heart and Diabetes Institute and the University of Cambridge.