A new study published in the April issue of Nature Genetics provides a predictive model that can identify sickle cell anemia (SCA) patients at risk of stroke with greater accuracy and faster than current methods allow, which may be useful as a prognostic test. Stroke is a major risk factor for sickle cell anemia patients under 20 years of age.
Paola Sebastiani, Marco Ramoni and colleagues analyzed 235 variations in 80 candidate genes in 1,398 sickle cell anemia patients, in order to develop a model that captured the genetic and clinical factors that influenced the risk of stroke. The authors validated the model in an independent population of 114 subjects, correctly predicting the occurrence of stroke with 98.2% accuracy.
The analysis found that 25 variations within 11 genes, combined with 4 clinical variables, interact to significantly influence the risk of stroke. These include some factors previously associated with stroke in the general population, including 3 genes in the TGF-beta pathway as well as hemoglobin levels. This provides evidence that stroke risk is a complex trait with multiple genetic and clinical influences, and suggests candidates that may be important in predicting stroke risk in the general population.
Currently, Transcranial Doppler (TCD) flow studies are used to predict the likelihood of stroke in children and young adults with SCA. However, the usefulness of this as a predictive test is limited, as only 10% of cases with abnormal TCD values will have a stroke, while some individuals with normal values will have a stroke.
Marco Ramoni (Harvard Medical School, Boston, MA, USA)
Paola Sebastiani (Boston University School of Public Health, Boston, MA, USA)
Also published online.
(C) Nature Genetics press release.
Message posted by: Trevor M. D'Souza