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                            Funding & Awards
 Use of MicroRNA Expression in DNA extracts to Predict Body Weight Class in Forensic Samples
Award Information
Awardee
              VIRGINIA COMMONWEALTH UNIVERSITY
Award #
              15PNIJ-23-GG-04212-MUMU
Funding Category
              Competitive Discretionary
Location
                    RICHMOND, VA
Congressional District
              4
Status
              Open
Funding First Awarded
              2023
Total funding (to date)
              $408,987
Original Solicitation
              NIJ FY23 Research and Development in Forensic Science for Criminal Justice Purposes
Description of original award (Fiscal Year 2023, $408,987)
ABSTRACT

Identification of phenotypic traits such as hair, skin and eye color along with biogeographic ancestry are rapidly becoming mainstream forensic analysis methods to provide investigative leads for unsolved criminal cases. Externally visible characteristics (EVCs) that include both genetic and environmental factors including facial structure, age, height and weight
have proven to be more difficult to accomplish, but remain important physical traits for identification of persons of interest to a case. While admittedly an imperfect measurement, estimation of body weight classification (underweight, normal, overweight, and obese) would provide important information for visual characterization of an unknown individual, whether that be an assailant for a crime or an unidentified victim. This area of characterization of body weight prediction of an individual from forensic evidence is completely unexplored.
    In our preliminary work, we have identified nine microRNA (miRNA) markers expressed and tested using DNA extracts of dried blood samples using Reverse Transcription-Quantitative PCR (RT-qPCR) that can predict classifications of body mass with 100% accuracy in a small sample set. The purpose of this project is to test those miRNA markers in a larger sampling of
the population, and to explore additional markers (if necessary) for improved accuracy. We will also test those markers and explore others for miRNAs that can predict body mass in saliva, as another commonly encountered body fluid in forensic samples. Evaluation and validation methods will utilize machine learning methods for classification modeling and utilize standard forensic developmental validation tests for precision, reliability, robustness, sensitivity and error rate, once accurate markers are identified in both body fluids.
The impact that this project will have on the forensic science community could be significant. Alone, body mass or weight classification is a minor advance for forensic biology; however, as part of a broader phenotypic panel (which is already available for use in casework), we begin to see a more comprehensive picture of the unknown person. By using DNA extracts
for determining miRNA expression for body weight class prediction, the stage is set for inclusion of the markers into a commercial high-throughput sequencing primer set that already includes other EVC markers. Ultimately, providing tools to DNA laboratories that can provide additional information about an unknown assailant or victim benefits society, the crime laboratory, and the criminal justice system by providing information to investigators for a more speedy and conclusive investigation. CA/NCF

  
Date Created: September 20, 2023
    
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