Exploring Eye, Hair, and Skin Pigmentation in a Spanish Population: Insights from Hirisplex-S Predictions

Area of Science:

• Genetics
• Forensic Science
• Human Biology

Background:

• Predicting human pigmentation is vital for identification.
• Genome-wide association studies (GWAS) identified numerous pigmentation-associated single nucleotide polymorphisms (SNPs).
• Genetic overlap exists among pigmentation traits, enabling predictive model development.

Purpose of the Study:

• To evaluate the HIrisPlex-S system's performance in predicting eye, hair, and skin color in a Spanish population.
• To assess the feasibility of reducing the number of SNPs used in pigmentation prediction models.

Main Methods:

• The HIrisPlex-S system was tested on 412 individuals.
• Model performance was evaluated using accuracy, AUC, sensitivity, specificity, and predictive values.
• Analysis focused on prediction accuracy for various pigmentation categories.

Main Results:

• High prediction accuracies (70-97%) were achieved for blue/brown eyes, brown hair, and intermediate skin.
• Challenges were observed in distinguishing intermediate eye colors, hair shades, and predicting dark/pale skin.
• The number of SNPs for eye color prediction could potentially be reduced to four without significant accuracy loss in this population.

Conclusions:

• Reducing the number of SNPs may be feasible for certain pigmentation predictions without compromising accuracy.
• Further validation in larger, diverse populations is necessary for broader generalizations.
• Future research should consider quantitative pigmentation for enhanced prediction accuracy.