The application discloses
atherosclerotic cardiovascular disease patient risk assessment based on blood microorganisms, and further discloses a
atherosclerotic cardiovascular disease prediction system, which comprises a sampling and layering module, a
microorganism sequencing module, an index detection module and a
data analysis module. The sampling and layering module divides samples into four groups, i.e., old men, old women, middle-aged men and middle-aged women, according to age / sex, and each group contains more than 100 ASCVD patients and more than 50 healthy controls. The
microorganism sequencing module generates equal-length fragments by digesting
DNA through BcgI
enzyme digestion, connects the equal-length fragments through a
linker, amplifies the equal-length fragments through PCR, and constructs a
microorganism tag
database (2b-Tag-DB) through Illumina sequencing. The index detection module analyzes traditional risk indexes such as
blood cell classification,
blood lipids and
inflammatory factors. The
data analysis module calculates the microorganism Gscore value, screens Gscore>5 species, and carries out
diversity analysis in combination with Chao1 / Shannon index and UniFrac / MetaStorms
algorithm. The prediction model module integrates the microorganism characteristics and the traditional indexes to generate a risk prediction result. The
system significantly improves the ASCVD risk prediction accuracy through the collaborative analysis of the
microbiome and the clinical indexes.