Calculating LRs for presence of body fluids from mRNA assay data in mixtures

An overview of log likelihood ratio cost in forensic science - Where is it used and what values can we expect?

There is increasing support for reporting evidential strength as a likelihood ratio (LR) and increasing interest in (semi-)automated LR systems. The log-likelihood ratio cost (Cllr) is a popular metric for such systems, penalizing misleading LRs further from 1 more. Cllr = 0 indicates perfection while Cllr = 1 indicates an uninformative system. However, beyond this, what constitutes a "good" Cllr is unclear. Aiming to provide handles on when a Cllr is "good", we studied 136 publications on (semi-)automated LR systems. Results show Cllr use heavily depends on the field, e.g., being absent in DNA analysis. Despite more publications on automated LR systems over time, the proportion reporting Cllr remains stable. Noticeably, Cllr values lack clear patterns and depend on the area, analysis and dataset. As LR systems become more prevalent, comparing them becomes crucial. This is hampered by different studies using different datasets. We advocate using public benchmark datasets to advance the field.

Developmental validation of an mRNA kit: A 5-dye multiplex assay designed for body-fluid identification

Identifying the sources of biosamples found at crime scenes is crucial for forensic investigations. Among the markers used for body fluid identification (BFI), mRNA has emerged as a well-studied marker because of its high specificity and remarkable stability. Despite this potential, commercially available mRNA kits specifically designed for BFI are lacking. Therefore, we developed an mRNA kit that includes 21 specific mRNA markers of body fluids, along with three housekeeping genes for BFI, to identify four forensic-relevant fluids (blood, semen, saliva, and vaginal fluids). In this study, we tested 451 single-body-fluid samples, validated the universality of the mRNA kit, and obtained a gene expression profile. We performed the validation studies in triplicates and determined the sensitivity, specificity, stability, precision, and repeatability of the mRNA kit. The sensitivity of the kit was found to be 0.1 ng. Our validation process involved the examination of 59 RNA mixtures, 60 body fluids mixtures, and 20 casework samples, which further established the reliability of the kit. Furthermore, we constructed five classifiers that can handle single-body fluids and mixtures using this kit. The classifiers output possibility values and identify the specific body fluids of interest. Our results showed the reliability and suitability of the BFI kit, and the Random Forest classifier performed the best, with 94% precision. In conclusion, we developed an mRNA kit for BFI which can be a promising tool for forensic practice.

Machine learning applications in forensic DNA profiling: A critical review

Machine learning (ML) is a range of powerful computational algorithms capable of generating predictive models via intelligent autonomous analysis of relatively large and often unstructured data. ML has become an integral part of our daily lives with a plethora of applications, including web, business, automotive industry, clinical diagnostics, scientific research, and more recently, forensic science. In the field of forensic DNA, the manual analysis of complex data can be challenging, time-consuming, and error-prone. The integration of novel ML-based methods may aid in streamlining this process while maintaining the high accuracy and reproducibility required for forensic tools. Due to the relative novelty of such applications, the forensic community is largely unaware of ML capabilities and limitations. Furthermore, computer science and ML professionals are often unfamiliar with the forensic science field and its specific requirements. This manuscript offers a brief introduction to the capabilities of machine learning methods and their applications in the context of forensic DNA analysis and offers a critical review of the current literature in this rapidly developing field.

Partial validation of multiplexed real-time quantitative PCR assays for forensic body fluid identification

Confirmatory body fluid identification using messenger RNA (mRNA) is a well-established technique to address issues encountered with conventional testing - such as poor sensitivity, specificity, and a lack of available tests for all body fluids of interest. For over a decade, endpoint reverse-transcription polymerase chain reaction (RT-PCR) assays have been used in forensic casework for such purposes. However, in comparison with real-time quantitative RT-PCR (RT-qPCR), endpoint RT-PCR has lower sensitivity, precision, and linear dynamic range. This research details the multiplexing and partial validation of confirmatory RT-qPCR assays. We have previously described novel assays for a range of body fluid targets and identified an optimal commercial kit for their amplification. Here, multiplexing was undertaken to form three assays: circulatory blood (SLC4A1) and menstrual fluid (STC1), saliva (HTN3) and vaginal material (CYP2B7P), and spermatozoa (PRM1) and seminal fluid (KLK2), all including a synthetic internal control RNA. Partial validation of the multiplexed assays incorporated the MIQE guidelines, ISO requirements, and SWGDAM guidelines. Using receiver operating characteristic (ROC) curves, each marker was significantly different from an uninformative assay and optimal cut-offs were all above 35 cycles. All assays showed a wide LDR (ranging from 3 to 5 logs with most R2 > 0.99), and high precision (most mean CV < 1 %). STC1 showed some instances of sporadic expression in blood, semen, and vaginal material at high CT values. CYP2B7P showed off-target expression in semen and blood. The sensitivities were approximated as; saliva: 1 in 1,000 dilution of a whole buccal swab, circulatory blood: 0.01-0.1 µL blood, menstrual fluid: 1 in 10,000 dilution of a whole menstrual swab, spermatozoa: 0.001 µL semen, seminal fluid: 0.01 µL semen, and vaginal material: 1 in 1,000 dilution of a whole vaginal swab. A total of 16 mock body fluid extract mixtures and 18 swab mixtures were tested and had 100% and 99% detection of target markers below each specific cut-off, respectively. Some mixtures containing high volumes of blood and semen showed off-target CYP2B7P expression. The successful application of a probabilistic model to the RT-qPCR data was also demonstrated. Further work will involve full developmental validation.

Promising applications of human-derived saliva biomarker testing in clinical diagnostics

Saliva testing is a vital method for clinical applications, for its noninvasive features, richness in substances, and the huge amount. Due to its direct anatomical connection with oral, digestive, and endocrine systems, clinical usage of saliva testing for these diseases is promising. Furthermore, for other diseases that seeming to have no correlations with saliva, such as neurodegenerative diseases and psychological diseases, researchers also reckon saliva informative. Tremendous papers are being produced in this field. Updated summaries of recent literature give newcomers a shortcut to have a grasp of this topic. Here, we focused on recent research about saliva biomarkers that are derived from humans, not from other organisms. The review mostly addresses the proceedings from 2016 to 2022, to shed light on the promising usage of saliva testing in clinical diagnostics. We recap the recent advances following the category of different types of biomarkers, such as intracellular DNA, RNA, proteins and intercellular exosomes, cell-free DNA, to give a comprehensive impression of saliva biomarker testing.

Objectifying evidence evaluation for gunshot residue comparisons using machine learning on criminal case data

Comparative gunshot residue analysis addresses relevant forensic questions such as 'did suspect X fire shot Y?'. More formally, it weighs the evidence for hypotheses of the form H₁: gunshot residue particles found on suspect's hands are from the same source as the gunshot residue particles found on the crime scene and H₂: two sets of particles are from different sources. Currently, experts perform this analysis by evaluating the elemental composition of the particles using their knowledge and experience. The aim of this study is to construct a likelihood-ratio (LR) system based on representative data. Such an LR system can support the expert by making the interpretation of the results of electron microscopy analysis more empirically grounded. In this study we chose statistical models from the machine learning literature as candidates to construct this system, as these models have been shown to work well for large and high-dimensional datasets. Using a subsequent calibration step ensured that the system outputs well-calibrated LRs. The system is developed and validated on casework data and an additional validation step is performed on an independent dataset of cartridge data. The results show that the system performs well on both datasets. We discuss future work needed before the method can be implemented in casework.

DNA Transfer in Forensic Science: Recent Progress towards Meeting Challenges

Understanding the factors that may impact the transfer, persistence, prevalence and recovery of DNA (DNA-TPPR), and the availability of data to assign probabilities to DNA quantities and profile types being obtained given particular scenarios and circumstances, is paramount when performing, and giving guidance on, evaluations of DNA findings given activity level propositions (activity level evaluations). In late 2018 and early 2019, three major reviews were published on aspects of DNA-TPPR, with each advocating the need for further research and other actions to support the conduct of DNA-related activity level evaluations. Here, we look at how challenges are being met, primarily by providing a synopsis of DNA-TPPR-related articles published since the conduct of these reviews and briefly exploring some of the actions taken by industry stakeholders towards addressing identified gaps. Much has been carried out in recent years, and efforts continue, to meet the challenges to continually improve the capacity of forensic experts to provide the guidance sought by the judiciary with respect to the transfer of DNA.

On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime

Body fluid and body tissue identification are important in forensic science as they can provide key evidence in a criminal investigation and may assist the court in reaching conclusions. Establishing a link between identifying the fluid or tissue and the DNA profile adds further weight to this evidence. Many forensic laboratories retain techniques for the identification of biological fluids that have been widely used for some time. More recently, many different biomarkers and technologies have been proposed for identification of body fluids and tissues of forensic relevance some of which are now used in forensic casework. Here, we summarize the role of body fluid/ tissue identification in the evaluation of forensic evidence, describe how such evidence is detected at the crime scene and in the laboratory, elaborate different technologies available to do this, and reflect real life experiences. We explain how, by including this information, crucial links can be made to aid in the investigation and solution of crime.

Interpretation of DNA data within the context of UK forensic science - evaluation

Forensic DNA provides a striking contribution to the provision of justice worldwide. It has proven to be crucial in the investigative phase of an unsolved crime where a suspect needs to be identified, e.g. from a DNA database search both nationally and internationally. It is also a powerful tool in the assignment of evidential weight to the comparison of a profile of a person of interest and a crime scene profile. The focus of this document is the evaluation of autosomal profiles for criminal trials in the UK. A separate review covers investigation and evaluation of Y-STR profiles, investigation using autosomal profiles, kinship analysis, body identification and Forensic Genetic Genealogy investigations. In less than 40 years, forensic DNA profiling has developed from a specialist technique to everyday use. Borrowing on advances in genome typing technology, forensic DNA profiling has experienced a substantial increase in its sensitivity and informativeness. Alongside this development, novel interpretation methodologies have also been introduced. This document describes the state of the art and future advances in the interpretation of forensic DNA data.

In the context of forensic casework, are there meaningful metrics of the degree of calibration?

Forensic-evaluation systems should output likelihood-ratio values that are well calibrated. If they do not, their output will be misleading. Unless a forensic-evaluation system is intrinsically well-calibrated, it should be calibrated using a parsimonious parametric model that is trained using calibration data. The system should then be tested using validation data. Metrics of degree of calibration that are based on the pool-adjacent-violators (PAV) algorithm recalibrate the likelihood-ratio values calculated from the validation data. The PAV algorithm overfits on the validation data because it is both trained and tested on the validation data, and because it is a non-parametric model with weak constraints. For already-calibrated systems, PAV-based ostensive metrics of degree of calibration do not actually measure degree of calibration; they measure sampling variability between the calibration data and the validation data, and overfitting on the validation data. Monte Carlo simulations are used to demonstrate that this is the case. We therefore argue that, in the context of casework, PAV-based metrics are not meaningful metrics of degree of calibration; however, we also argue that, in the context of casework, a metric of degree of calibration is not required.