Publikationsliste – Københavns Universitet

Retsmedicin > Publikationer > Publikationsliste

Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Ewelina Pośpiech, Yan Chen, Magdalena Kukla-Bartoszek, Krystal Breslin, Anastasia Aliferi, Jeppe D. Andersen, David Ballard, Lakshmi Chaitanya, Ana Freire-Aradas, Kristiaan J. van der Gaag, Lorena Girón-Santamaría, Theresa E. Gross, Mario Gysi, Gabriela Huber, Ana Mosquera-Miguel, Charanya Muralidharan, Małgorzata Skowron, Ángel Carracedo, Cordula Haas, Niels Morling & 18 andre Walther Parson, Christopher Phillips, Peter M. Schneider, Titia Sijen, Denise Syndercombe-Court, Marielle Vennemann, Sijie Wu, Shuhua Xu, Li Jin, Sijia Wang, Ghu Zhu, Nick G. Martin, Sarah E. Medland, Wojciech Branicki, Susan Walsh, Fan Liu, Manfred Kayser, EUROFORGEN-NoE Consortium

Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.

OriginalsprogEngelsk
TidsskriftForensic Science International: Genetics
Vol/bind37
Sider (fra-til)241-251
ISSN1872-4973
DOI
StatusUdgivet - 1 nov. 2018

ID: 203554466