DNA-based prediction of eye color in Latin American population applying Machine Learning models.

Journal: Computers in biology and medicine
Published Date: Aug 1, 2025

Abstract

Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relationship between the human genetic code and visible characteristics, diseases, and behaviors, among others. The aim of this study is to improve the prediction of eye color from genotype by means of several Machine Learning models, using a dataset of 308 volunteers from Buenos Aires, Argentina. The results achieved are competitive and demonstrate the usefulness of artificial intelligence (AI) in the fields of genetics and its application in areas such as health, biometrics and forensics.

Authors

  • Cristian A Martínez
    Lab. LITRP, Depto. DCI, Facultad de Ciencias de la Ingeniería, Universidad Católica del Maule, Av. San Miguel 3605, Talca, 3480112, Chile. Electronic address: cmartinez@di.unsa.edu.ar.
  • Diana M Hohl
    Lab. de Diversidad Genética, Instituto Multidisciplinario de Biología Celular (CONICET-UNLP-CICPBA), Av. 526 y Camino Gral. Belgrano, La Plata, 1900, Buenos Aires, Argentina; Comisión de Investigaciones Científicas de la Provincia de Buenos Aires CICPBA, Av. 526 entre 10 y 11, La Plata, 1900, Buenos Aires, Argentina.
  • María de Los A Gutiérrez
    Centro de Investigaciones del Medio Ambiente (CONICET-UNLP-CICPBA), Boulevard 120 N(o) 1489, La Plata, 1900, Buenos Aires, Argentina.
  • Sagnik Palmal
    Université de Lille, INSERM, CHU Lille, institut pasteur de Lille, U1167-RID-AGE, Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France.
  • Pierre Faux
    GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France.
  • Kaustubh Adhikari
    School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom.
  • Rolando Gonzalez-Jose
    Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Bv. Almirante Brown 2915, Puerto Madryn, U9120ACD, Chubut, Argentina.
  • Maria C Bortolini
    Instituto de Biociências, Universidad Federal do Rio Grande do Sul, Av. Paulo Gama 110, Porto Alegre, 90040-060, Rio Grande do Sul, Brazil.
  • Victor Acuña-Alonzo
    National Institute of Anthropology and History, 135 Hamburgo, Mexico City, 06600, Mexico.
  • Carla Gallo
    Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Av. Honorio Delgado 430, Lima, 15102, Peru.
  • Andres Ruiz Linares
    Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 220 Handan Road, Shanghai, 200434, China; ADES (Anthropologie Bio-Culturelle, Droit, Éthique et Santé), UFR de Médecine, Aix-Marseille University, 58 Blvd Charles Livon, Marseille, 13007, France; Department of Genetics, Evolution and Environment and UCL Genetics Institute, University College London, London, WC1E 6BT, United Kingdom.
  • Francisco Rothhammer
    Instituto de Alta Investigación, Tarapacá University, 2222 18 de Septiembre Av, Arica, 1000000, Chile.
  • Cecilia I Catanesi
    Lab. de Diversidad Genética, Instituto Multidisciplinario de Biología Celular (CONICET-UNLP-CICPBA), Av. 526 y Camino Gral. Belgrano, La Plata, 1900, Buenos Aires, Argentina; Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, Calle 122 y 60, La Plata, 1900, Buenos Aires, Argentina.
  • Ricardo J Barrientos
    Lab. LITRP, Depto. DCI, Facultad de Ciencias de la Ingeniería, Universidad Católica del Maule, Av. San Miguel 3605, Talca, 3480112, Chile.

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