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

Research output: Contribution to journalJournal articleResearchpeer-review

  • Ewelina Pośpiech
  • Yan Chen
  • Magdalena Kukla-Bartoszek
  • Krystal Breslin
  • Anastasia Aliferi
  • Andersen, Jeppe Dyrberg
  • 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
  • Morling, Niels
  • 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.

Original languageEnglish
JournalForensic Science International: Genetics
Pages (from-to)241-251
Publication statusPublished - 1 Nov 2018

    Research areas

  • DNA prediction, Externally visible characteristics, Forensic DNA Phenotyping, Hair shape, Head hair, Targeted massively parallel sequencing

ID: 203554466