Immune Response Differentiates Malaria from Other Infections

Malaria affects around 200 million people around the world but its non-specific symptoms, coupled with a lack of access to testing facilities, mean it is difficult to distinguish from other infectious diseases.

Treating malaria promptly not only increases a patient's chances of survival, but also helps prevent the disease from spreading to more people and could ultimately speed up malaria diagnosis and treatment. Analyzing a patient’s immune response could be central to quickly and accurately diagnosing malaria.

Scientists at Stanford University combine the data already available from 40 previous studies, bringing together more than 3,000 blood samples from patients with various infectious diseases. This included some from patients who were known to have malaria, some from patients with other common tropical diseases such as dengue, typhoid, or leishmaniasis, and some from healthy volunteers.

The team combined the data, which allowed them to study the activity of more than 6,000 different genes. They used a computer to trawl through 2,100 of the samples and look for patterns of gene expression. They found that a group of seven genes showed a different pattern of expression in patients with malaria, compared with healthy people and patients with other infectious diseases. Once the pattern of expression of these genes had been identified, the scientists tested it out on the remaining 900 samples from patients with different tropical diseases and from healthy people. They found that the pattern could distinguish malaria samples from the others with 96% accuracy.

Purvesh Khatri, PhD, an assistant professor and lead investigator of the study said, “We know that the immune system is able to deploy different tactics for fighting different infections such as bacteria, viruses and the malaria parasite. This study shows that we can detect signs of these differences by looking at which genes are being expressed, and we think it is possible to use this knowledge to speed up diagnosis and treatment.” The study was presented at the 27th European Congress of Clinical Microbiology and Infectious Diseases, held April 22-25, 2017, in Vienna, Austria.