Translational Informatics in Smart Healthcare

Yi Shen, Sheng Zhang, Jie Zhou, Jiajia Chen

Cohort studies are observational studies in which the investigator determines the exposure status of subjects and then follows them for subsequent outcomes. The incidence of outcomes is observed in the exposed group and compared with that in a nonexposed group. Recently, new epidemiologic strategies have encouraged cohort research information exchange and cooperation to improve the cognition of disease etiology, such as case-cohort design and nested case-control study, which is available for "omics" data. Meanwhile, large-scale cohort studies using a prospective multiple design and long follow-ups have explored some of the challenges in preventive medicine. Cohort study can bridge the gap between the micro and macro research.This chapter is divided into three parts: 1. Basic knowledge of cohort study, which included the definition of cohort study and different types of cohort study, how to design the cohort study, data analysis for the cohort study, sources of bias in cohort studies, tools and software for cohort studies, and strengths and limitations of cohort study 2. Cohort study for "omics" data analysis, which introduced three related methodologically distinct study designs, case-cohort design for genomic cohort study, nested case-control design for transcriptomics cohort data, and population-based design for integrative "omics" cohort 3. Perspectives on cohort study including data-driven medicine and cohort research, cohort research for healthcare medicine, and cohort research for preventive medicine.