000145378 001__ 145378 000145378 005__ 20241024135331.0 000145378 0247_ $$2doi$$a10.3390/genes15101330 000145378 0248_ $$2sideral$$a140199 000145378 037__ $$aART-2024-140199 000145378 041__ $$aeng 000145378 100__ $$aNavarro-López, B 000145378 245__ $$aunderstanding and predicting human pigmentation traits is crucial for individual identification. genome-wide association studies have revealed numerous pigmentation-associated SNPs, indicating genetic overlap among pigmentation traits and offering the potential to develop predictive models without t 000145378 260__ $$c2024 000145378 5060_ $$aAccess copy available to the general public$$fUnrestricted 000145378 5203_ $$aUnderstanding and predicting human pigmentation traits is crucial for individual identification. Genome-wide association studies have revealed numerous pigmentation-associated SNPs, indicating genetic overlap among pigmentation traits and offering the potential to develop predictive models without the need for analyzing large numbers of SNPs. Methods: In this study, we assessed the performance of the HIrisPlex-S system, which predicts eye, hair, and skin color, on 412 individuals from the Spanish population. Model performance was calculated using metrics including accuracy, area under the curve, sensitivity, specificity, and positive and negative predictive value. Results: Our results showed high prediction accuracies (70% to 97%) for blue and brown eyes, brown hair, and intermediate skin. However, challenges arose with the remaining categories. The model had difficulty distinguishing between intermediate eye colors and similar shades of hair and exhibited a significant percentage of individuals with incorrectly predicted dark and pale skin, emphasizing the importance of careful interpretation of final predictions. Future studies considering quantitative pigmentation may achieve more accurate predictions by not relying on categories. Furthermore, our findings suggested that not all previously established SNPs showed a significant association with pigmentation in our population. For instance, the number of markers used for eye color prediction could be reduced to four while still maintaining reasonable predictive accuracy within our population. Conclusions: Overall, our results suggest that it may be possible to reduce the number of SNPs used in some cases without compromising accuracy. However, further validation in larger and more diverse populations is essential to draw firm conclusions and make broader generalizations. 000145378 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000145378 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000145378 700__ $$aBaeta M 000145378 700__ $$aSuárez-Ulloa V 000145378 700__ $$aMartos-Fernández 5 000145378 700__ $$aMoreno-López O 000145378 700__ $$0(orcid)0000-0001-6469-9189$$aMartínez-Jarreta B$$uUniversidad de Zaragoza 000145378 700__ $$aJiménez S, Olalde I 000145378 700__ $$aMartínez de Pancorbo, M.A.$$uUniversidad de Zaragoza 000145378 7102_ $$11012$$2613$$aUniversidad de Zaragoza$$bDpto. Farmac.Fisiol.y Med.L.F.$$cÁrea Medicina Legal y Forense 000145378 773__ $$g15, 1330 (2024), [19 pp.]$$pGenes (Basel)$$tGenes$$x2073-4425 000145378 8564_ $$s837171$$uhttps://zaguan.unizar.es/record/145378/files/texto_completo.pdf$$yVersión publicada 000145378 8564_ $$s2644165$$uhttps://zaguan.unizar.es/record/145378/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000145378 909CO $$ooai:zaguan.unizar.es:145378$$particulos$$pdriver 000145378 951__ $$a2024-10-24-12:11:38 000145378 980__ $$aARTICLE