Plasma proteomics provides better insight into severe childhood malaria

05 December 2012

Scientists at NIMR and in Ibadan, Nigeria have shown that an accurate definition of the major childhood malaria syndromes can be achieved using plasma proteome-patterns. The research is published in PLOS ONE.

Human malaria caused by Plasmodium falciparum results in 300 million clinical episodes annually, leading to one million deaths. 85% of the cases and 90% of the mortality occurs in sub-Saharan Africa, mostly amongst children. Nigeria accounts for a quarter of the global cases and a third of the malaria-attributable childhood deaths. Cerebral malaria and severe malarial anemia are the most serious life-threatening clinical syndromes of Plasmodium falciparum infection in childhood.

WHO case definitions for severe malaria are sensitive and useful for clinical diagnosis, but they lack the specificity required to be able to carry out studies aimed at understanding the pathogenesis of clinically different forms of childhood malaria. Previous studies have attempted, with mixed success, to define malaria syndromes by studying plasma correlates of severity. Different host responses to infection are likely to be reflected in plasma proteome-patterns, providing indicators of the pathogenesis of these syndromes. High-throughput plasma proteome profiling enables simultaneous analysis of a large number of samples. This approach allows the use of statistical pattern-recognition methods to discover and validate proteome-patterns that can discriminate disease states.

Delmiro Fernandez-Reyes (pictured), in the Division of Parasitology, has collaborated with researchers in the College of Medicine in the University of Ibadan, Nigeria. They used a systems approach to define the plasma proteome profile during malaria infection and to identify distinctive patterns that are characteristic of different disease states. As part of a prospective case-control study of severe childhood malaria at the main tertiary hospital of the city of Ibadan, in Nigeria, plasma and comprehensive clinical data for a total of 946 children were obtained and plasma was subjected to high-throughput proteomic profiling. Distinctive plasma proteome-patterns accurately distinguished children with cerebral malaria and with severe malarial anemia from the uncomplicated cases and also from well or unwell children without malaria. Malaria infection introduces distinguishable changes in the plasma proteome of children as seen by the striking differences between the malaria-negative controls and the malaria-positive children groups. The large cohorts allowed them to statistically validate the pattern-based proteome definitions of the major childhood malaria syndromes.

The lack of specific childhood malaria definitions has limited the progress on understanding the pathology of the major severe syndromes. Our study confirms that there are proteome changes characteristic of the clinical malarial syndromes with a new level of accuracy. To the best of our knowledge this study is the first to show that a panel of proteins, defined as a proteome-pattern, dissects clinical malaria syndromes. We now know that we can use the plasma proteome to define biomarkers of severity. The further development of this technique for use at the point of care could have a tremendous impact in the management of these patients, allowing a clinician to decide which patients are more likely to develop a severe infection. Our findings provide a starting point to refine the current WHO definitions of these syndromes, which lack the necessary specificity to further study severe malaria pathogenesis.

Delmiro Fernandez-Reyes

Visualization of community control children versus other study groups.

Visualization of community control children versus other study groups.

Click image to view at full-size

Each sphere represents an individual child proteome profile plotted in 3D space defined by the first three principal components. CM = Cerebral Malaria (red); SMA = Severe Malarial Anemia (purple); UM = Uncomplicated Malaria (yellow); DC = Disease Controls (blue); CC = Community Controls (green).
(a.) CC vs. CM; (b.) CC vs. SMA; (c.) CC vs UM and (d.) CC vs. DC.

Original article

Florence Burté, Biobele J., Adebola E., Wasiu A. Ajetunmobi, Francesca Battaglia, Barry K. Ely, Nathaniel K. Afolabi, Dimitrios Athanasakis, Francis Akinkunmi, Olayinka Kowobari, Samuel Omokhodion, Kikelomo Osinusi, Felix O. Akinbami, Wuraola A., Olugbemiro Sodeinde, Delmiro Fernandez-Reyes (2012)

Severe childhood malaria syndromes defined by plasma proteome profiles

PLOS ONE  7(12): e49778 Full text.

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