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Published on: October 6, 2020
Application of Linear Regression Model of Gpnmb Gene in Rat Injury Time Estimation
Yan-Ru Xi1, Yuan-Xin Liu1, Na Feng1
1School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
Objectives:
To investigate the effects of injury time, postmortem interval (PMI) and postmortem storage temperature on mRNA expression of glycoprotein non-metastatic melanoma protein B (Gpnmb), and to establish a linear regression model between Gpnmb mRNA expression and injury time, to provide aimed at providing potential indexes for injury time estimation.
Methods:
Test group SD rats were anesthetized and subjected to blunt contusion and randomly divided into 0 h, 4 h, 8 h, 12 h, 16 h, 20 h and 24 h groups after injury, with 18 rats in each group. After cervical dislocation, 6 rats in each group were collected and stored at 0 ℃, 16 ℃ and 26 ℃, respectively. The muscle tissue samples of quadriceps femoris injury were collected at 0 h, 12 h and 24 h postmortem at the same temperature. The grouping method and treatment method of the rats in the validation group were the same as above. The expression of Gpnmb mRNA in rat skeletal muscle was detected by RT-qPCR. The Pearson correlation coefficient was used to evaluate the correlation between Gpnmb mRNA expression and injury time, PMI, and postmortem storage temperature. SPSS 25.0 software was used to construct a linear regression model, and the validation group data was used for the back-substitution test.
Results:
The expression of Gpnmb mRNA continued to increase with the prolongation of injury time, and the expression level was highly correlated with injury time (P<0.05), but had little correlation with PMI and postmortem storage temperature (P>0.05). The linear regression equation between injury time (y) and Gpnmb mRNA relative expression (x) was y=0.611 x+4.489. The back-substitution test proved that the prediction of the model was accurate.
Conclusions:
The expression of Gpnmb mRNA is almost not affected by the PMI and postmortem storage temperature, but is mainly related to the time of injury. Therefore, a linear regression model can be established to infer the time of injury.
Insights
Glycoprotein non-metastatic melanoma protein B (Gpnmb) mRNA expression increases with injury time in rats. This finding allows for the development of a linear regression model to accurately estimate injury time.
Area of Science:
- Forensic Science
- Molecular Biology
- Biomarker Research
Background:
- Estimating time since injury is crucial in forensic investigations.
- Biomarkers for postmortem interval estimation are actively sought.
- Gene expression changes offer potential indicators of biological events.
Purpose of the Study:
- To assess the impact of injury time, postmortem interval (PMI), and storage temperature on Gpnmb mRNA expression.
- To develop a predictive model for injury time estimation based on Gpnmb mRNA levels.
Main Methods:
- SD rats were subjected to blunt contusion, with samples collected at various time points post-injury and postmortem.
- Gpnmb mRNA expression was quantified using RT-qPCR.
- Linear regression analysis was employed to model the relationship between Gpnmb mRNA and injury time.
Main Results:
- Gpnmb mRNA expression significantly correlated with time since injury (P<0.05).
- PMI and postmortem storage temperature showed minimal correlation with Gpnmb mRNA levels (P>0.05).
- A validated linear regression model (y=0.611x+4.489) accurately predicted injury time.
Conclusions:
- Gpnmb mRNA expression is a reliable indicator of injury time, largely independent of PMI and storage conditions.
- The established linear regression model provides a viable tool for forensic injury time estimation.
