Body odour may help identify malaria: study

Changes in the body odour may help identify people infected with malaria, even when they show no symptoms of the disease, a study has found.

Blood tests do not necessarily pick up infection with the plasmodium parasite, especially at low parasite densities, according to the study published in the journal Proceedings of the National Academy of Sciences.

DNA tests for the parasite usually show infection, but they are far from rapid.

"Our previous work in a mouse model found that malaria infection altered the odours of infected mice in ways that made them more attractive to mosquitoes, particularly at a stage of infection where the transmissible stage of the parasite was present at high levels," said Consuelo De Moraes, adjunct professor at the Pennsylvania State University in the US.

"We also found long-term changes in the odour profiles of infected mice," said Moraes.

The researchers wanted to see if they could identify changes in human odours associated with malaria infection that might be useful for diagnosing infected individuals.

They were particularly interested in identifying those who were infected, but had no symptoms.

The researchers initially used microscopy and an SD Bioline Rapid Diagnostic Test to identify patients with malaria.

Since these methods have limited sensitivity, particularly when parasite loads are low, infections were confirmed by DNA tests.

They identified 333 people who unambiguously were either infected with malaria or were not infected with malaria.

Only if both microscopy and DNA studies were negative were subjects considered malaria-free.

In some later analyses, the researchers included 77 people who were positive for malaria according to DNA, but showed no parasites in the microscopic tests.

Malaria infection does not create new volatile chemicals in the body, but alters the amounts - up or down - of volatile chemicals that are already present in the odours of healthy people.

"It is interesting that the symptomatic and asymptomatic infections were different from each other as well as from healthy people," said Mark C Mescher, a professor at ETH Zurich in Switzerland.

This difference among infected, infected asymptomatic, and healthy individuals may eventually lead to tests capable of rapidly and accurately identifying infected people, even those without symptoms.

The researchers found that predictive models using machine learning reliably identify infection status based on volatile biomarkers.

"Our models identified asymptomatic infections with 100 per cent sensitivity, even in the case of low-level infections not detectable by microscopy," the researchers said.

These results far exceed any currently available rapid diagnostic tests, they said.