A combined CXCL10, CXCL8 and H-FABP panel for the staging of human African trypanosomiasis patients

Identification of stage biomarkers for human African trypanosomiasis

Human African trypanosomiasis (HAT), caused by infection with sub-species of Trypanosoma brucei (T. b.), manifests as a hemolymphatic stage followed by an encephalitic stage. The distinction of the two stages needs improvement as drugs used for the late stage are highly toxic. Transcripts encoding 16 secreted proteins differentially expressed in the brains of mice at late stage T. b. brucei infection when the early stage drug suramin is no longer effective and different to immunoglobulins, chemokines, and cytokines, were selected by microarray analysis. Lipocalin 2 and secretory leukocyte peptidase inhibitor (SLPI) mRNA showed the highest differential expression in mice. These transcripts were also upregulated in brains from infected rats. Lipocalin 2 was increased in cerebrospinal fluid (CSF) from rats during late stage T. b. brucei infection. Protein levels of lipocalin 2, SLPI, and the chemokine CXCL10 were found increased in CSF from Trypanosoma brucei gambiense and Trypanosoma brucei rhodesiense late stage HAT compared to early stage.

Emerging trends in the diagnosis of Human African Trypanosomiasis

Human African trypanosomiasis (HAT) or sleeping sickness is caused by protozoan parasitesTrypanosoma brucei gambienseandT. b. rhodesiense. Despite the enormous technological progress in molecular parasitology in recent years, the diagnosis of HAT is still problematic due to the lack of specific tools. To date, there are two realities when it comes to HAT; the first one being the world of modern experimental laboratories, equipped with the latest state-of-the-art technology, and the second being the world of HAT diagnosis, where the latest semi-commercial test was introduced 30 years ago (Magnuset al.1978). Hence, it appears that the lack of progress in HAT diagnosis is not primarily due to a lack of scientific interest or a lack of research funds, but mainly results from the many obstacles encountered in the translation of basic research into field-applicable diagnostics. This review will provide an overview of current diagnostic methods and highlight specific difficulties in solving the shortcomings of these methods. Future perspectives for accurate, robust, affordable diagnostics will be discussed as well.

Bioinformatics for protein biomarker panel classification: what is needed to bring biomarker panels into in vitro diagnostics?

A large number of biomarkers have been discovered over the past few years using proteomics techniques. Unfortunately, most of them are neither specific nor sensitive enough to be translated into in vitro diagnostics and routine clinical practice. From this observation, the idea of combining several markers into panels to improve clinical performances has emerged. In this article, we present a discussion of the bioinformatics aspects of biomarker panels and the concomitant challenges, including high dimensionality and low patient number and reproducibility.