Multi-omics landscape and machine learning predictors of acute and chronic coronary syndrome diagnosis in young patients

With the rapid development of China's economy, changes in diet structure, lifestyle and excessive mental pressure have led to a younger trend in the incidence of ACUTE coronary syndrome, and the mortality rate has been on the rise, especially in Shenzhen, the country with the youngest average age.Coronary heart disease among young people not only reduces the quality of life and loses the ability to work, but also prematurely consumes medical resources and increases social costs, bringing heavy burdens to families and society.Therefore, it is of great significance to conduct researches on the transcription, metabolism and microbiome of young patients with ACUTE coronary syndrome and obtain the multi-group characteristics of these patients for early warning, guiding the improvement of life style, regulating treatment, improving treatment rate, and reducing family and social burden. Research purpose and significance In recent years, with the rapid development of China's economy, the changes in dietary structure and lifestyle, as well as excessive mental stress, and other factors have led to an obvious trend of younger incidence of Coronary artery disease (CAD), and an increase in the death rate.This is especially true in Shenzhen, which has the youngest average age in the country.CAD in young people not only reduces the quality of life and loses the ability to work, but also prematurely consumes medical resources, increases social costs, and brings heavy burden to families and society.Therefore, it is of great significance to study the transcriptome, metabolome and intestinal flora of young CAD and obtain the multiomic characteristics of these patients for early warning, guiding the improvement of lifestyle, regulating treatment, improving treatment rate, and reducing the burden of family and society.