NEW YORK (Reuters Health) - An analytic model that includes 31 single nucleotide polymorphisms (SNPs) that interact with fetal hemoglobin can predict stroke in patients with sickle cell anemia (SCA) with 98.2% accuracy, according to a new report.
“Although further investigation is required to establish the causative role of these genetic markers, our results support the emerging hypothesis that stroke in individuals with SCA is a complex trait caused the interaction of multiple genes,” study co-author Dr. Marco F. Ramoni, from Harvard Medical School in Boston, and colleagues note.
As reported in the March 20th online issue of Nature Genetics, the researchers used Bayesian networks to analyze 108 SNPs in 39 candidate genes in nearly 1400 SCA patients. From this, the uncovered 31 SNPs in 12 genes that seemed to influence stroke risk.
Among the implicated genes were three that were involved in the TGF-beta pathway and a gene called SELP that has been linked to stroke in the general population.
As noted, in a test group of 114 SCA patients, the final analytic model was able to predict stroke with 98.2% accuracy.
Given the tie to SELP and other genes previously linked to stroke, the authors believe that the current findings could have implications for stroke patients, in general, not just those with SCA. “Our model may offer some insights into the genetic basis of the third leading cause of death in the US,” they add.
Source: Nature Genetics 2005. [ Google search on this article ]
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