Mathematical modelling using predictive biomarkers for the outcome of canine Leishmaniasis upon chemotherapy

Prediction parameters of possible outcomes of canine leishmaniasis (CanL) therapy might help with therapeutic decisions and animal health care. Here, we aimed to develop a diagnostic method with predictive value by analyzing two groups of dogs with CanL, those that exhibited a decrease in parasite load upon antiparasitic treatment (group: responders) and those that maintained high parasite load despite the treatment (group: non-responders). The parameters analyzed were parasitic load determined by q-PCR, hemogram, serum biochemistry and immune system-related gene expression signature. A mathematical model was applied to the analysis of these parameters to predict how efficient their response to therapy would be. Responder dogs restored hematological and biochemical parameters to the reference values and exhibited a Th1 cell activation profile with a linear tendency to reach mild clinical alteration stages. Differently, non-responders developed a mixed Th1/Th2 response and exhibited markers of liver and kidney injury. Erythrocyte counts and serum phosphorus were identified as predictive markers of therapeutic response at an early period of assessment of CanL. The results presented in this study are highly encouraging and may represent a new paradigm for future assistance to clinicians to interfere precociously in the therapeutic approach, with a more precise definition in the patient’s prognosis. This work was funded by the Brazilian agencies Bahia Research Foundation—FAPESB (Grant nº PRONEM 498/2011-PNE 0002/2011 to S.M.B-M), National Council for Scientific and Technological Development —CNPq (PQ scholarship nº 307813/2018-5 to SMBM, and nº 303621/2015-0 to HG) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior —CAPES (PDSE scholarship nº 88881.189587/2018-01 to R.S.G; Finance Code 001 and PV scholarship nº 23066.033859/2018-73 to R.S.). This work was supported by grants from CESPU (TramTap-CESPU-2016, Chronic-TramTap_CESPU_2017 and TraTapMDMA-CESPU-2018), from the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013), funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and the Fundação para a Ciência e Tecnologia (FCT) (contract IF/00021/2014 to R.S.), Infect-Era (project INLEISH to R.S.) and Proyecto SNIP N◦ 292900 “Creación del Servicio de Laborato