Identification of five types of forensic body fluids based on stepwise discriminant analysis

Peripheral blood, menstrual blood, semen, saliva and vaginal secretions are the five most common body fluids found at crime scenes, and the identification of these five body fluids is of great significance to the reconstruction of a crime scene and resolution of the case. However, accurate identification of these five body fluids is still a challenge. To address this problem, a mathematical model for differentiating five types of forensic body fluids based on the differential expression characteristics of multiple miRNAs in five body fluids (peripheral blood, menstrual blood, semen, saliva and vaginal secretions) was developed. A total of 350 forensic body fluids (70 of each type) were collected and tested, and relative expression of 10 miRNAs (miR-451a, miR-205-5p, miR-203-3p, miR-214-3p, miR-144-3p, miR-144-5p, miR-654-5p, miR-888-5p, miR-891a-5p, miR-124a-3p) in all samples was detected by SYBR Green real-time qPCR. Three hundred samples (60 samples of each body fluid) were used as the training set to screen meaningful identification markers by stepwise discriminant analysis, and a discriminant function was established. Fifty samples (10 samples of each body fluid) were used as a validation set to examine the accuracy of the model, and 25 samples (the types of samples were unknown to the experimenter) were used for a blind test. Except for miR-144-3p, the other miRNAs were selected to construct discriminant analysis models. The self-validation accuracy of the model was 99.7 %, cross-validation accuracy was 99.3 %, accuracy of the identification validation set was 100 %, and accuracy of the blind test result was 100 %. This study provides a reliable and accurate identification strategy for five common body fluids (peripheral blood, menstrual blood, semen, saliva, and vaginal secretions) in forensic medicine.