TY - JOUR
T1 - Towards broadening Forensic DNA Phenotyping beyond pigmentation
T2 - Improving the prediction of head hair shape from DNA
AU - Pośpiech, Ewelina
AU - Chen, Yan
AU - Kukla-Bartoszek, Magdalena
AU - Breslin, Krystal
AU - Aliferi, Anastasia
AU - Andersen, Jeppe D.
AU - Ballard, David
AU - Chaitanya, Lakshmi
AU - Freire-Aradas, Ana
AU - van der Gaag, Kristiaan J.
AU - Girón-Santamaría, Lorena
AU - Gross, Theresa E.
AU - Gysi, Mario
AU - Huber, Gabriela
AU - Mosquera-Miguel, Ana
AU - Muralidharan, Charanya
AU - Skowron, Małgorzata
AU - Carracedo, Ángel
AU - Haas, Cordula
AU - Morling, Niels
AU - Parson, Walther
AU - Phillips, Christopher
AU - Schneider, Peter M.
AU - Sijen, Titia
AU - Syndercombe-Court, Denise
AU - Vennemann, Marielle
AU - Wu, Sijie
AU - Xu, Shuhua
AU - Jin, Li
AU - Wang, Sijia
AU - Zhu, Ghu
AU - Martin, Nick G.
AU - Medland, Sarah E.
AU - Branicki, Wojciech
AU - Walsh, Susan
AU - Liu, Fan
AU - Kayser, Manfred
AU - EUROFORGEN-NoE Consortium
PY - 2018/11/1
Y1 - 2018/11/1
N2 - 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.
AB - 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.
KW - DNA prediction
KW - Externally visible characteristics
KW - Forensic DNA Phenotyping
KW - Hair shape
KW - Head hair
KW - Targeted massively parallel sequencing
UR - http://www.scopus.com/inward/record.url?scp=85053904609&partnerID=8YFLogxK
U2 - 10.1016/j.fsigen.2018.08.017
DO - 10.1016/j.fsigen.2018.08.017
M3 - Journal article
C2 - 30268682
AN - SCOPUS:85053904609
SN - 1872-4973
VL - 37
SP - 241
EP - 251
JO - Forensic Science International: Genetics
JF - Forensic Science International: Genetics
ER -