Study finds: Body odor can help determine malarial infection

Detecting the symptomatic carriers of malaria is not an easy job. It requires a lot of careful examinations by collecting the blood samples in order to look at the parasites. But when it comes to identifying the asymptomatic carriers, it becomes more difficult and challenging. The infected carriers do not come with any clinical symptoms as well but still act as reservoirs that help the disease to spread more.

The international research team took a step more to find out a way to diagnose the asymptomatic malaria carriers and the key to finding turned out to be in the body odor. Consuelo De Moraes, a researcher of this study claims that their previous work in a mouse model found that malaria infection altered the odors of infected mice in ways that eventually made them more attractive to mosquitoes, particularly at a stage of infection where the transmissible stage of the parasite was present at high levels.

The latest study focused only to uncover the odor-related biomarkers that could be identified in humans either with symptomatic or asymptomatic malaria infections. The blood and skin samples were collected from over 400 school children from the malarial prone areas in western Kenya. Because of the limited sensitivity of examining malaria using microscopy, the research also concluded with the infections with the help of DNA tests.

There were skin volatility profiles constructed for every individual with the help of gas chromatography-mass spectrometry. This step enabled the scientists and researchers to clearly find out the odor profiles based on the volatility of the skin by comparing the malaria-free subjects with either the symptomatic or the asymptomatic infections.

Mark C. Mescher, a scientist working on this study had to say that it is quite interesting that the symptomatic and the asymptomatic infections were different from each other as well as from the healthy people. The data was later used to the creative predictive models with the help of machine learning to reliably examine and identify the human subjects that have the disease infected.

If you believe the results, the models can now determine the asymptomatic infections with accurate sensitivity. They can pick up the infections even from the low-level malarial cases that the microscopy results could not find out.

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