No abstract

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. In this study, we investigate the role of gender as a factor that contributes to eye colour variation and suggest that the gender effect on eye colour is population specific.A total of 230 Italian individuals were typed for the six IrisPlex SNPs (rs12913832, rs1800407, rs12896399, rs1393350, rs16891982 and rs12203592). A quantitative eye colour score (Pixel Index of the Eye: PIE-score) was calculated based on digital eye images using the custom made DIAT software. The results were compared with those of Danish and Swedish population samples.As expected, we found HERC2 rs12913832 as the main predictor of human eye colour independently of ancestry. Furthermore, we found gender to be significantly associated with quantitative eye colour measurements in the Italian population sample. We found that the association was statistically significant only among Italian individuals typed as heterozygote GA for HERC2 rs12913832. Interestingly, we did not observe the same association in the Danish and Swedish population. This indicated that the gender effect on eye colour is population specific. We estimated the effect of gender on quantitative eye colour in the Italian population sample to be 4.9%. Among gender and the IrisPlex SNPs, gender ranked as the second most important predictor of human eye colour variation in Italians after HERC2 rs12913832. We, furthermore, tested the five lower ranked IrisPlex predictors, and evaluated all possible 3 6 (729) genotype combinations of the IrisPlex assay and their corresponding predictive values using the IrisPlex prediction model [4]. The results suggested that maximum three (rs12913832, rs1800407, rs16891982) of the six IrisPlex SNPs are useful in practical forensic genetic casework.

Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

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.

BackgroundThe color of the eyes is one of the most prominent phenotypes in humans and it is often used to describe the appearance of an individual. The intensity of pigmentation in the iris is strongly associated with one single‐nucleotide polymorphism (SNP), rs12913832:A>G that is located in the promotor region of OCA2 (OMIM #611409). Nevertheless, many eye colors cannot be explained by only considering rs12913832:A>G.MethodsIn this study, we searched for additional variants in OCA2 to explain human eye color by sequencing a 500 kbp region, encompassing OCA2 and its promotor region.ResultsWe identified three nonsynonymous OCA2 variants as important for eye color, including rs1800407:G>A (p.Arg419Gln) and two variants, rs74653330:A>T (p.Ala481Thr) and rs121918166:G>A (p.Val443Ile), not previously described as important for eye color variation. It was shown that estimated haplotypes consisting of four variants (rs12913832:A>G, rs1800407:G>A (p.Arg419Gln), rs74653330:A>T (p.Ala481Thr), and rs121918166:G>A (p.Val443Ile)) explained 75.6% (adjusted R 2 = 0.76) of normal eye color variation, whereas rs12913832:A>G alone explained 68.8% (adjusted R 2 = 0.69). Moreover, rs74653330:A>T (p.Ala481Thr) and rs121918166:G>A (p.Val443Ile) had a measurable effect on quantitative skin color (P = 0.008).ConclusionOur data showed that rs74653330:A>T (p.Ala481Thr) and rs121918166:G>A (p.Val443Ile) have a measurable effect on normal pigmentation variation.