Our poster was a presentation of the preliminary results of the data coming from the “Mother and Child Determinants of Pediatric Dengue and Development of a Risk Assessment Scoring System for Severe Disease among Filipino Children” Project of the Research and Development Center for Maternal and Child Health (ReDMatCH) Program under the Center for Research and Development, Davao Medical School Foundation Inc. The results primarily highlight both the statistically and biologically significant metabolites that explain dengue severity among children one month to 14 years old. We used urine serum samples and analyzed to Waters Xevo G3 Quadrupole Time-of-Flight (QTOF) Mass Spectrometer, then Waters Acquity Ultra Performance Liquid Chromatography (UPLC) I-Class System, then to Progenesis QI software. The resulting data was then subjected to several advanced statistical methods such as Principal Component Analysis, Partial Least Squares-Discriminant Analysis, Fold Change Analysis, ANOVA, and Elastic Net Regression. This is to understand how changes in metabolites influence the severity of dengue, and pinpoint which of these metabolites play a major role in the disease. See more here.

Abstract

Severe dengue is a leading cause of serious illness and death, most especially in Asia, particularly in the Philippines. To date, no study has yet explored the role of metabolomes on a child’s response to dengue infection, however several indirect evidence already point towards such direction. This study aimed to determine the metabolomic profile using urine samples pediatric patients (severe and non-severe), and healthy control groups. A prospective cohort study of serologically diagnosed patients and healthy controls was conducted. The participants were children between one month and 14 years old from select regions of southern Philippines. Known and unknown serum metabolites were determined via untargeted metabolomics. A total of 32,529 metabolites were found from 143 pediatric patients. Of whom, 44 had severe dengue, 45 had non-severe dengue, and 54 were healthy. Results show an overlapping characteristic between the former two groups, while a slightly different characteristic for the healthy group. Results also show five metabolites having a variable importance of at least four point five indicating the extreme contribution of these metabolites in the discrimination between the groups. Eighty percent of these unannotated metabolites are highly abundant in children with severe and non-severe dengue, while having very low abundance on healthy controls. Two of these metabolites are 30% more abundant in children with severe and non-severe dengue than healthy children. Lastly, elastic net regression results show one metabolite that increases the odds, by 8%, of children having severe dengue compared to healthy children. Moreover, another metabolite increase the odds, by 20%, of children having non-severe dengue compared to healthy children. Our findings identified key metabolites associated with children having severe dengue, non-severe dengue, and healthy groups. This highlights targeted interventions focusing on the to-be-annotated metabolites to reduce the risk of patients to develop severe dengue.