Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans. (November 2015) - Pośpiech, Ewelina; Karłowska-Pik, Joanna; Marcińska, Magdalena; Abidi, Sarah; Andersen, Jeppe Dyrberg; Berge, Margreet van den; Carracedo, Ángel; Eduardoff, Mayra; Freire-Aradas, Ana; Morling, Niels; Sijen, Titia; Skowron, Małgorzata; et al.
Highlights: A replication study was made of SNPs most closely associated with hair morphology variation in Europeans (assigning straight, wavy and curly hair phenotypes). Analysis of 670 samples from seven European populations revealed the strongest association for rs11803731 in TCHH, rs7349332 in WNT10A and rs1268789 in FRAS1 . Applying three different mathematical models to assess the predictive capacity of the SNPs indicated neural networks gives the best performing model to predict straight hair with high sensitivity and better specificity than logistic regression and CRT methods. The combined TTGGGG SNP genotype (rs11803731-rs7349332-rs1268789) was identified as the best predictor, giving greater than 80% probability of straight hair. The reported study is the first assessment of the forensic suitability of hair morphology as an externally visible characteristic. The results provide the basis for extended analyses of SNPs associated with this trait. Abstract: DNA-based prediction of hair morphology, defined as straight, curly or wavy hair, could contribute to an improved description of an unknown offender and allow more accurate forensic reconstructions of physical appearance in the field of forensic DNA phenotyping. Differences in scalp hair morphology are significant at the worldwide scale and within Europe. The only genome-wide association study made to date revealed the Trichohyalin gene ( TCHH ) to be significantly associated with hair morphology in Europeans and reported weaker associations for WNT10A and FRAS1 genes. We conducted a study that centered on six SNPs located in these three genes with a sample of 528 individuals from Poland. The predictive capacity of the candidate DNA variants was evaluated using logistic regression; classification and regression trees; and neural networks, by applying a 10-fold cross validation procedure. Additionally, an independent test set of 142 males from six European populations was used to verify performance of the developed prediction models. Our study confirmed association of rs11803731 ( TCHH), rs7349332 ( WNT10A) and rs1268789 ( FRAS1 ) SNPs with hair morphology. The combined genotype risk score for straight hair had an odds ratio of 2.7 and these predictors explained ∼8.2% of the total variance. The selected three SNPs were found to predict straight hair with a high sensitivity but low specificity when a 10-fold cross validation procedure was applied and the best results were obtained using the neural networks approach (AUC = 0.688, sensitivity = 91.2%, specificity = 23.0%). Application of the neural networks model with 65% probability threshold on an additional test set gave high sensitivity (81.4%) and improved specificity (50.0%) with a total of 78.7% correct calls, but a high non-classification rate (66.9%). The combined TTGGGG SNP genotype for rs11803731, rs7349332, rs1268789 (European frequency = 4.5%) of all six straight hair-associated alleles was identified as the best predictor, giving >80% probability of straight hair. Finally, association testing of 44 SNPs previously identified to be associated with male pattern baldness revealed a suggestive association with hair morphology for rs4679955 on 3q25.1. The study results reported provide the starting point for the development of a predictive test for hair morphology in Europeans. More studies are now needed to discover additional determinants of hair morphology to improve the predictive accuracy of this trait in forensic analysis.