The invention relates to a biomarker of periapical cells and application of the biomarker, and belongs to the technical field of biological detection. The objective of the invention is to solve the problem that a conventional periodontal
cell marker has expression overlap with other interstitial cells under an anoxic condition, cannot accurately distinguish tip periodontal
cell subgroups, and hinders functional research and
targeted therapy development thereof. The method comprises the following steps: screening 15 specific genes (including
Adamts9, Cd93, Ctla2a,
Fkbp1a, Angpt2 and the like) as periapical
cell biomarkers by adopting
machine learning according to brain
single cell sequencing data of a high-altitude hypoxia mouse; and constructing a
logistic regression prediction model to realize cell identification. According to the biomarker combination and the biomarker model, the
false detection rate (lt; 5%). A new
molecular marker for accurately identifying periapical cells is developed through a
machine learning method based on a
big data set, and a brand new breakthrough is provided for developing
hypoxia response type periapical
cell specific markers and functional targets.