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Research reveals genes predicting the density of dengue fever



A group of 20 genes determines the response of humans to the deng, which can be predicted with 80% accuracy if it is more likely that the person will suffer the most severe form of this disease, a study published on Tuesday said.

Thus, authors at the Stanford University of California (USA) believe that there is an open path to the prevention of this infection that affects between 200 and 400 million people worldwide every year and this causes about half a million deaths.

The researchers focused on the common genetic characteristics of patients who showed cases of dengue fever from advanced to severe.

The report, published in the scientific journal Cell Reports, analyzed data from five previous studies, where 20 genes were highlighted in all patients who developed severe cases of illness.

"We did not compare healthy patients with infected patients, we compared those who had uncomplicated dengue infection with those who developed a heavy dengue," said Purvesh Khatri, a professor of medicine and biomedical data at Stanford School of Medicine. author of studies.

In this way, the researchers have been able to identify a group of genes that make it possible to find out whether the patient is more likely to get worse with this disease, spreading by the bite of mosquitoes, mostly known as "Aedes aegypti".

In order to confirm the validity of the identified genes, the researchers conducted a joint analysis with the Clinical Research Center in Valencia, Calif.

In the initial stages, 34 participants with binge were evaluated, and 20 of the previously identified genes predicted the development of the infection.

The results were fully consistent with the effective diagnosis of who would most likely develop the infection and who did not.

"Of course, this population sample is small and we want to confirm our data in larger populations," said Khatri, pointing out that Paragva will be developing a new phase of the study.

With a larger sample of populations there is also the potential to improve data, which could potentially lead to a decrease in the number of genes, "said Shirit Einav, Stanford Professor of Medicine and Microbiology and Immunology, and co-author of the study.


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