The preliminary study on the combined application model of serum miRNAs in the diagnosis of pneumoconiosis

Abstract

Objective: To explore the role of serum microRNA (miRNAs) levels in the detection of pneumoconiosis, and to establish a combined application model of multiple serums miRNAs for pneumoconiosis diagnosis. Methods: 152 cases were selected in the case group and the control group respectively. The TaqMan Low Density Array method was used to screen out the candidate miRNAs for early screening of pneumoconiosis, and RT-qPCR was used to verify. According to the area under the curve (AUC) , the sensitivity and specificity of the candidate indicators were investigated. The logistic regression model was established by the two-class logistic regression model. Results: The expression of 7 candidate miRNAs in the serum of pneumoconiosis patients was significantly different (P<0.05) . The receiver operating curve (ROC) of the above 7 miRNAs was analyzed, miRNA-21, miRNA-200c, miRNA-16, miRNA-206, miRNA-155, miRNA-29a had statistical significance, and their ROC-AUC is 0.629~0.932. Logistic regression model was: logitP=13.769+0.536×miRNA-21-0.878×miRNA-200C-0.012×miRNA-16-0.111×miRNA-206+0.117×miRNA-155-1.192×miRNA-29a. Conclusion: Multiple serum miRNAs combined application models may be used for the diagnosis of pneumoconiosis patients.