Unveiling disease dynamics: longitudinal plasma protein profiling in a Plasmodium falciparum malaria cohort for enhanced patient stratification and severity assessment

Introduction

Malaria remains a major global burden with more than 200 million symptomatic cases leading to 600 000 deaths every year. Infection with the malaria-causing parasite Plasmodium falciparum can result in mild or severe forms of the disease, with less severe symptoms associated with previous repeated infections. The pathology itself is partly a result of the immune response to the blood stage of the disease, which triggers a strong inflammatory reaction. Here, we aim to use a systems-level approach to comprehensively describe the plasma protein profiles in clinical malaria and their association with the disease.

Methods

Here, we investigated the peripheral immune response of symptomatic patients in a well-characterized cohort of 72 returning travelers treated for P. falciparum malaria at Karolinska University Hospital. Using Proximity Extension Assay (PEA) by Olink, we profiled 1463 proteins in plasma at acute disease and follow-up samples up to one year after treatment without reinfection. To infer the cellular source and possible targets of the proteins, we used a single-cell multi-omics approach on PBMCs to assess the transcriptional profiles in a subset of donors. Finally, the proteomic data enabled a cohort stratification that associated proteomic profiles with disease severity in patients.

Results

Clinical malaria caused a strong perturbation of the plasma protein profile, resulting in more than 800 differentially abundant proteins compared with convalescent samples. Many of these proteins are predicted to be secreted to blood, indicating a specific role in the immune response, especially in cytokine–cytokine receptor interaction. Analysis of single-cell profiles revealed that innate immune cells seem to be the main source and target of several highly affected proteins. The plasma proteomic profiles stratified the patients into three groups associated with disease severity as determined by the sequential organ failure assessment (SOFA) score. We propose a protein signature that is distinct for severe malaria compared to other febrile infections.

Conclusion

Next-generation plasma profiling combined with transcriptomics on immune cells and extensive clinical data enabled us to investigate the immune response to natural symptomatic malaria to an unprecedented level and identify proteins associated with clinical presentation. Our work confirms, extends, and provides a useful resource for better understanding of the systemic immune response to malaria and connects it to clinical outcomes and other molecular parameters.

Importance

Thanks to the development of novel omics technologies, precious patient samples can be profiled for increasing numbers of parameters. This allowed us to study the host response in patients with malaria to an unprecedented level, enabling us to deepen our understanding of the response, identify novel drivers of disease severity, and suggest new therapeutic targets.