The invention belongs to the technical field of biological
medicine, and particularly discloses a multi-
protein marker combination for
intervertebral disc degeneration prediction and severity evaluation and a
machine learning
algorithm. The marker combination comprises any three or more of COL6 [alpha] 3, REG1beta, ATF5, CAP1, MAGEA4 and LILRB3, and preferably six proteins are combined for use. And quantitatively detecting the expression level of the
protein in the
blood plasma through
enzyme-linked immunosorbent
assay (ELISA), constructing a prediction model in combination with a binary
Logistic regression algorithm, and outputting an
intervertebral disc degeneration grading result. Experiments show that the AUC (
area under curve) of joint detection of six proteins reaches 0.870, which is averagely improved by 11.8% compared with that of single
protein detection, and the AUC is obviously superior to that of an existing imaging grading method. According to the present invention, the
intervertebral disc degeneration
plasma protein diagnosis
system is established based on the SOMAscan technology for the first time, the
protein concentration threshold of the ELISA
verification is provided, the efficient
complementation with the MRI Pfirrmann grading is achieved, the advantages of noninvasive property, objective property and high sensitivity are provided, and the new method is provided for the clinical early screening and
dynamic monitoring.