Combining mechanism-based prediction with patient-based profiling for psoriasis metabolomics biomarker discovery.

Combining mechanism-based prediction with patient-based profiling for psoriasis metabolomics biomarker discovery. AMIA Annu Symp Proc. 2017;2017:1734-1743 Authors: Wang Q, McCormick TS, Ward NL, Cooper KD, Conic R, Xu R Abstract Psoriasis is a chronic, debilitating skin condition that affects approximately 125 million individuals worldwide. The cause of psoriasis appears multifactorial, and no unified mitigating signal or single antigenic target has been identified to date. Metabolomic studies hold great potential for explaining disease mechanism, facilitating early diagnosis, and identifying potential therapeutic areas. Here, we present an integrated disease metabolomic biomarker discovery strategy that combines mechanism-based biomarker discovery with clinical sample-based metabolomic profiling. We applied this strategy in identifying and understanding metabolite biomarkers for psoriasis. The key innovation of our strategy is a novel mechanism-based metabolite prediction system, mmPredict, which assimilates vast amounts of existing knowledge of diseases and metabolites. mmPredict first constructed a psoriasis-specific mouse mutational phenotype profile. It then constructed phenotype profiles for a total of 259,170 chemicals/metabolites using known chemical genetics and human metabolomic data. Metabolites were then prioritized based on the phenotypic similarities between disease- and metabolites. We evaluated mmPredict using 150 met...
Source: AMIA Annual Symposium Proceedings - Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research