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                            Funding & Awards
 Ensuring standards and enhancing the field of predictive biometrics using a globally-diverse genotype-phenotype database
Award Information
Awardee
              TRUSTEES OF INDIANA UNIVERSITY
Award #
              2018-DU-BX-0219
Funding Category
              Competitive Discretionary
Location
                    INDIANAPOLIS, IN
Congressional District
              7
Status
              Closed
Funding First Awarded
              2018
Total funding (to date)
              $651,242
Original Solicitation
              NIJ FY18 Research and Development in Forensic Science for Criminal Justice Purposes
Description of original award (Fiscal Year 2018, $651,242)
Forensic DNA phenotyping or Predictive Biometrics from DNA as it is also coined, is the ability to predict ones physical appearance using biological material. It has the potential to significantly complement current DNA analyses practice within forensic laboratories in the United States and worldwide. In order to move towards the implementation of these new DNA analyses methods in current casework, there must be several developments that this proposal addresses to relay any concerns for forensic practitioners and the community. First, prediction models need to represent individuals from varying populations. Models should reflect the more global genetic variation seen here in the United States and worldwide for more accurate and reliable predictions. The first aim is to produce a more global database resource to use in future physical appearance prediction modeling. Second, as fundamental research progresses, so too will the idea of individualized physical appearance prediction, and although not there yet, standards need to be set in place now. The second aim is to form a Predictive Biometrics Reference (PBR) set that contains a more global representative set of individuals (version 1 n=100) with genotypic and phenotypic data that researchers in the field can compare new model performances with a standardized reference set. This set will allow full transparency on the performance of any prediction systems on the same set of individuals. All prediction model performance comparisons shall then be published online for the community to see. Third, the genes and variants associated with physical appearance traits and their prediction is expanding, therefore the technology for generating all-in-one biological assays in a forensic setting must also be updated. Massive Parallel Sequencing (MPS) technology on next generation sequencers allows the generation of hundreds of genotypes in one protocol. The third aim is to design predictive biometrics assays for forensic usage. This in conjunction with the expected update to DNA technology in forensic laboratories using bench-top sequencers may be the final push the forensic community needs to begin using these tools. Lastly, researcher  practitioner relationships give invaluable direction to research as it provides insight into what is needed, and allowed in a forensic setting. Aim four is to continuing cultivating a relationship between the two, a university laboratory and state police laboratory, to discuss research progress and to assess how established forensic DNA phenotyping methods (e.g. HIrisPlex-S) for physical appearance prediction can impact current and cold casework (n=10) within the state.
This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR  200.210(a)(14).
CA/NCF



  
Grant-Funded Publications
        
                      Exploring regional aspects of 3D facial variation within European individuals
                  Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morphology
                  Matching 3D Facial Shape to Demographic Properties by Geometric Metric Learning: A Part-Based Approach
                  3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies
                  Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations
                  Evaluation of supervised machine-learning methods for predicting appearance traits from DNA
                  Shared heritability of human face and brain shape
                  Large-scale open-source three-dimensional growth curves for clinical facial assessment and objective description of facial dysmorphism
                  Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits
                  The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits
                  The Intersection of the Genetic Architectures of Orofacial Clefts and Normal Facial Variation
                  Insights into the genetic architecture of the human face

  
Date Created: September 27, 2018
    
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