For eye color, the focus was understanding green or intermediate eye color; in terms of hair color, the focus was on understanding age-related hair color changes; and the focus on skin color pertained to both categorical and quantitative prediction systems, since there was no system in place at the time of this project. There were three parts to this study: 1) proposal of a new and highly specific genome-wide association study (GWAS); 2) assessment of the most predictive SNPs for quantitative eye, hair, and skin color; and 3) development of a user-friendly computer software that would enable users to input genotype information to produce a highly specific quantitative color result for eye, hair, and skin. Due to some of the work from this grant project (more to come), categorical eye, hair, and skin color prediction is now available for forensic practitioners in a forensically developmentally validated assay, along with an online web tool for prediction at http://hirisplex.erasmusmc.nl. Forensic practitioners can obtain intelligence information on eye, hair, and skin color on any case by using these validated and published tools. During this grant project, work has been done for several agencies in their investigation of three cold cases with reference to a suspect's eye, hair, and skin color. There has not yet been any reported results from these analyses. Project design and methods are described. A listing is provided of publications and products from this grant.
Improving the Prediction of Human Quantitative Pigmentation Traits such as Eye, Hair and Skin Color using a Worldwide Representation Panel of US and European Individuals
NCJ Number
253066
Date Published
July 2018
Length
12 pages
Annotation
This is the Final Summary Overview of the findings, methodology, and criminal justice implications of a research project that sought to improve the prediction of human quantitative pigmentation traits of eye, hair, and skin color, using a worldwide representation panel of U.S. and European individuals.
Abstract
Date Published: July 1, 2018