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A systematic analysis of miRNA markers and classification algorithms for forensic body fluid identification
Yang Liu1, Hongxia He2, Zhi-Xiong Xiao3
1College of Life Sciences, Sichuan University, China.
Abstract:
Identifying the types of body fluids left at the crime scene can be essential to reconstructing the crime scene and inferring criminal behavior. MicroRNA (miRNA) molecule extracted from the trace of body fluids is one of the most promising biomarkers for the identification due to its high expression, extreme stability and tissue specificity. However, the detection of miRNA markers is not the answer to a yes-no question but the probability of an assumption. Therefore, it is a crucial task to develop complicated methods combining multi-miRNAs as well as computational algorithms to achieve the goal. In this study, we systematically analyzed the expression of 10 most probable body fluid-specific miRNA markers (miR-451a, miR-205-5p, miR-203a-3p, miR-214-3p, miR-144-3p, miR-144-5p, miR-654-5p, miR-888-5p, miR-891a-5p and miR-124-3p) in 605 body fluids-related samples, including peripheral blood, menstrual blood, saliva, semen and vaginal secretion. We introduced the kernel density estimation (KDE) method and six well-established methods to classify the body fluids in order to find the most optimal combinations of miRNA markers as well as the corresponding classifying method. The results show that the combination of miR-451a, miR-891a-5p, miR-144-5p and miR-203a-3p together with KDE can achieve the most accurate and robust performance according to the cross-validation, independent tests and random perturbation tests. This systematic analysis suggests a reference scheme for the identification of body fluids in an accurate and stable manner.
Insights
Forensic science can identify body fluids using microRNA (miRNA) markers. A combination of four specific miRNAs and the kernel density estimation (KDE) method provides accurate and stable body fluid identification.
Area of Science:
- Forensic Science
- Molecular Biology
- Biochemistry
Background:
- Identifying body fluids at crime scenes is crucial for reconstructing events and inferring behavior.
- MicroRNAs (miRNAs) are highly stable, tissue-specific biomarkers promising for body fluid identification.
- Current miRNA detection provides probabilistic results, necessitating advanced methods for accurate classification.
Purpose of the Study:
- To systematically analyze the expression of 10 body fluid-specific miRNA markers.
- To evaluate multiple computational methods for classifying body fluids based on miRNA profiles.
- To identify optimal miRNA combinations and classification methods for robust body fluid identification.
Main Methods:
- Analysis of 605 body fluid samples (blood, saliva, semen, vaginal secretions).
- Expression profiling of 10 selected miRNA markers.
- Application of kernel density estimation (KDE) and six other classification algorithms.
Main Results:
- A specific combination of four miRNAs (miR-451a, miR-891a-5p, miR-144-5p, miR-203a-3p) demonstrated superior performance.
- The kernel density estimation (KDE) method, paired with these miRNAs, achieved the highest accuracy and robustness.
- Validation through cross-validation, independent tests, and random perturbation tests confirmed reliability.
Conclusions:
- The combination of miR-451a, miR-891a-5p, miR-144-5p, and miR-203a-3p with KDE offers a reliable method for body fluid identification.
- This systematic approach provides a reference scheme for accurate and stable forensic body fluid analysis.
- Advanced computational methods combined with multi-miRNA analysis enhance forensic investigations.
