Biomarkers of infection with consistent discriminating power for diagnosis and/or prognosis are keystones for efficient therapeutic management of diseases. The protozoan Trypanosoma cruzi, the etiologic agent of Chagas disease (CD), exhibits high clinical and genetic diversity, making it difficult to define biomarkers. In animal models of infection, as well as in patients, many different outcomes have been described. Thus, pathophysiogenesis parameters were highly variable in patients and even in inbred animals, which impeded reliable one-dimensional diagnosis/prognosis. To help solve those problems, an in-depth analysis of the similarities and differences in the CD caused by different parasite strains or different patient conditions is needed. Multidimensional statistics may overcome the high variability for each individual parameter in patients and even in inbred animals, revealing some pathophysiological patterns that accurately allow diagnosis of clinical and physiopathological characteristics. Here, we describe this type of method and its application to T. cruzi infection.
Keywords: Absolute quantification; Biomarkers; Linear discriminant analysis; Trypanosoma cruzi.