Could a transcriptomic signature predict the survival likelihood of Ebola patients?
William Aryitey |
The West African Ebola outbreak of 2014 was the largest epidemic of the disease in recorded history (1). Though the prevalence has declined, it remains difficult to differentiate between those diagnosed cases that may be fatal, from those that are not. In a bid to fill that gap, a team of investigators has made a discovery that may just help, by revealing that transcriptomic analysis can yield mechanisms of pathogenesis in Ebola patients (2) – information that helps produce a clearer prognosis.
“Initially, the goal was to sequence the virus in blood samples to track its evolution and to determine how this would inform both epidemiology and therapeutics,” says Julian Hiscox, lead researcher and Chair in infection and global health at the University of Liverpool. “We realized the same approaches could be used to look not only at the virus, but also at what was happening inside an infected patient.” To gain additional insight, the researchers looked into the transcriptomic profiles of 30,000–40,000 genes in infected patients and found that fatalities of the disease displayed a stronger upregulation of interferon signaling, whereas patients who survived showed an increased presence of natural killer cells. Transcriptomic analysis allowed the researchers to pinpoint a panel of various genes that triggered these changes and more, and used them as “strong predictors of patient outcome, independent of viral load” (2).
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- Centers for Disease Control and Prevention, “2014-2016 Ebola outbreak in West Africa”, (2016). Available at: bit.ly/2k1MklY. Accessed February 8, 2017.
- X Liu et al., “Transcriptomic signatures differentiate survival from fatal outcomes in humans infected with Ebola virus”, Genome Biol, 18, 4 (2017). PMID: 28100256.