Data-driven microbiota biomarker discovery for personalized drug therapy of cardiovascular disease. (November 2020)

• Record Type: Journal Article
• Authors: Shen, Li; Shen, Ke; Bai, Jinwei; Wang, Jiao; Singla, Rajeev K.; Shen, Bairong
• Is Part Of: Pharmacological research. Volume 161(2020)
• Publication Date: 2020-11
• Subjects: Cardiovascular disease -- Computer aided biomarker discovery -- Microbiota -- Personalized drug therapy -- Translational informatics; Pharmacology -- Periodicals; Pharmacology -- Periodicals; Research -- Periodicals; Médicaments -- Recherche -- Périodiques; Pharmacologie -- Périodiques; 615.105
• DOI: 10.1016/j.phrs.2020.105225
• Languages: English
• ISSNs: 1043-6618

Abstract

Graphical abstract: Abstract: Cardiovascular disease (CVD) is the most wide-spread disorder all over the world. The personalized and precision diagnosis, treatment and prevention of CVD is still a challenge. With the developing of metagenome sequencing technologies and the paradigm shifting to data-driven discovery in life science, the computer aided microbiota biomarker discovery for CVD is becoming reality. We here summarize the data resources, knowledgebases and computational models available for CVD microbiota biomarker discovery, and review the present status of the findings about the microbiota patterns associated with the therapeutic effects on CVD. The future challenges and opportunities of the translational informatics on the personalized drug usages in CVD diagnosis, prognosis and treatment are also discussed.