Perception of blue and brown eye colours for forensic DNA phenotyping

Predictive accuracy of genetic variants for eye color in a Kazakh population using the IrisPlex system

OBJECTIVE

This study assesses the accuracy of the IrisPlex system, a genetic eye color prediction tool for forensic analysis, in the Kazakh population. The study compares previously published genotypes of 515 Kazakh individuals from varied geographical and ethnohistorical contexts with phenotypic data on their eye color, introduced for the first time in this research.

RESULTS

The IrisPlex panel's effectiveness in predicting eye color in the Kazakh population was validated. It exhibited slightly lower accuracy than in Western European populations but was higher than in Siberian populations. The sensitivity was notably high for brown-eyed individuals (0.99), but further research is needed for blue and intermediate eye colors. This study establishes IrisPlex as a useful predictive tool in the Kazakh population and provides a basis for future investigations into the genetic basis of phenotypic variations in this diverse population.

Association between Variants in the OCA2-HERC2 Region and Blue Eye Colour in HERC2 rs12913832 AA and AG Individuals

The OCA2-HERC2 region is strongly associated with human pigmentation, especially eye colour. The HERC2 SNP rs12913832 is currently the best-known predictor for blue and brown eye colour. However, in a previous study we found that 43 of 166 Norwegians with the brown eye colour genotype rs12913832:AA or AG, did not have the expected brown eye colour. In this study, we carried out massively parallel sequencing of a ~500 kbp HERC2-OCA2 region in 94 rs12913832:AA and AG Norwegians (43 blue-eyed and 51 brown-eyed) to search for novel blue eye colour variants. The new candidate variants were subsequently typed in a Norwegian biobank population (total n = 519) for population specific association analysis. We identified five new variants, rs74409036:A, rs78544415:T, rs72714116:T, rs191109490:C and rs551217952:C, to be the most promising candidates for explaining blue eye colour in individuals with the rs12913832:AA and AG genotype. Additionally, we confirmed the association of the missense variants rs74653330:T and rs121918166:T with blue eye colour, and observed lighter skin colour in rs74653330:T individuals. In total, 37 (86%) of the 43 blue-eyed rs12913832:AA and AG Norwegians could potentially be explained by these seven variants, and we suggest including them in future prediction models.

Applicability of the IrisPlex system for eye color prediction in an admixed population from Argentina

Eye color prediction based on an individual's genetic information is of interest in the field of forensic genetics. In recent years, researchers have studied different genes and markers associated with this externally visible characteristic and have developed methods for its prediction. The IrisPlex represents a validated tool for homogeneous populations, though its applicability in populations of mixed ancestry is limited, mainly regarding the prediction of intermediate eye colors. With the aim of validating the applicability of this system in an admixed population from Argentina (n = 302), we analyzed the six single nucleotide variants used in that multiplex for eye color and four additional SNPs, and evaluated its prediction ability. We also performed a genotype-phenotype association analysis. This system proved to be useful when dealing with the extreme ends of the eye color spectrum (blue and brown) but presented difficulties in determining the intermediate phenotypes (green), which were found in a large proportion of our population. We concluded that these genetic tools should be used with caution in admixed populations and that more studies are required in order to improve the prediction of intermediate phenotypes.

A new approach to broaden the range of eye colour identifiable by IrisPlex in DNA phenotyping

IrisPlex system represents the most popular model for eye colour prediction. Based on six polymorphisms this model provides very accurate predictions that strongly depend on the definition of eye colour phenotypes. The aim of the present study was to introduce a new approach to improve eye colour prediction using the well-validated IrisPlex system. A sample of 238 individuals from a Southern Italian population was collected and for each of them a high-resolution image of eye was obtained. By quantifying eye colour variation into CIELAB space several clustering algorithms were applied for eye colour classification. Predictions with the IrisPlex model were obtained using eye colour categories defined by both visual inspection and clustering algorithms. IrisPlex system predicted blue and brown eye colour with high accuracy while it was inefficient in the prediction of intermediate eye colour. Clustering-based eye colour resulted in a significantly increased accuracy of the model especially for brown eyes. Our results confirm the validity of the IrisPlex system for forensic purposes. Although the quantitative approach here proposed for eye colour definition slightly improves its prediction accuracy, further research is still required to improve the model particularly for the intermediate eye colour prediction.

Predicting eye and hair colour in a Norwegian population using Verogen's ForenSeq™ DNA signature prep kit

Prediction of eye and hair colour from DNA can be an important investigative tool in forensic cases if conventional DNA profiling fails to match DNA from any known suspects or cannot obtain a hit in a DNA database. The HIrisPlex model for simultaneous eye and hair colour predictions was developed for forensic usage. To genotype a DNA sample, massively parallel sequencing (MPS) has brought new possibilities to the analysis of forensic DNA samples. As part of an in-house validation, this study presents the genotyping and predictive performance of the HIrisPlex SNPs in a Norwegian study population, using Verogen's ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system and the HIrisPlex webtool. DNA-profiles were successfully typed with DNA input down to 125 pg. In samples with DNA input < 125 pg, false homozygotes were observed with as many as 92 reads. Prediction accuracies in terms of AUC were high for red (0.97) and black (0.93) hair colours, as well as blue (0.85) and brown (0.94) eye colours. The AUCs for blond (0.72) and brown (0.70) hair colour were considerably lower. None of the individuals was predicted to have intermediate eye colour. Therefore, the error rates of the overall eye colour predictions were 37% with no predictive probability threshold (pmax) and 26% with a probability threshold of 0.7. We also observed that more than half of the incorrect predictions were for individuals carrying the rs12913832 GG genotype. For hair colour, 65% of the individuals were correctly predicted when using the highest probability category approach. The main error was observed for individuals with brown hair colour that were predicted to have blond hair. Utilising the prediction guide approach increased the correct predictions to 75%. Assessment of phenotype-genotype associations of eye colours using a quantitative eye colour score (PIE-score), revealed that rs12913832 AA individuals of Norwegian descent had statistically significantly higher PIE-score (less brown eye colour) than individuals of non-northern European descent. To our knowledge, this has not been reported in other studies. Our study suggests that careful assessment of the target population prior to the implementation of forensic DNA phenotyping to case work is beneficial.

Prediction of Eye Colour in Scandinavians Using the EyeColour 11 (EC11) SNP Set

Description of a perpetrator's eye colour can be an important investigative lead in a forensic case with no apparent suspects. Herein, we present 11 SNPs (Eye Colour 11-EC11) that are important for eye colour prediction and eye colour prediction models for a two-category reporting system (blue and brown) and a three-category system (blue, intermediate, and brown). The EC11 SNPs were carefully selected from 44 pigmentary variants in seven genes previously found to be associated with eye colours in 757 Europeans (Danes, Swedes, and Italians). Mathematical models using three different reporting systems: a quantitative system (PIE-score), a two-category system (blue and brown), and a three-category system (blue, intermediate, brown) were used to rank the variants. SNPs with a sufficient mean variable importance (above 0.3%) were selected for EC11. Eye colour prediction models using the EC11 SNPs were developed using leave-one-out cross-validation (LOOCV) in an independent data set of 523 Norwegian individuals. Performance of the EC11 models for the two- and three-category system was compared with models based on the IrisPlex SNPs and the most important eye colour locus, rs12913832. We also compared model performances with the IrisPlex online tool (IrisPlex Web). The EC11 eye colour prediction models performed slightly better than the IrisPlex and rs12913832 models in all reporting systems and better than the IrisPlex Web in the three-category system. Three important points to consider prior to the implementation of eye colour prediction in a forensic genetic setting are discussed: (1) the reference population, (2) the SNP set, and (3) the reporting strategy.

Skin pigmentation and genetic variants in an admixed Brazilian population of primarily European ancestry

Although many genes have been shown to be associated with human pigmentary traits and forensic prediction assays exist (e.g. HIrisPlex-S), the genetic knowledge about skin colour remains incomplete. The highly admixed Brazilian population is an interesting study population for investigation of the complex genotype-phenotype architecture of human skin colour because of its large variation. Here, we compared variants in 22 pigmentary genes with quantitative skin pigmentation levels on the buttock, arm, and forehead areas of 266 genetically admixed Brazilian individuals. The genetic ancestry of each individual was estimated by typing 46 AIM-InDels. The mean proportion of genetic ancestry was 68.8% European, 20.8% Sub-Saharan African, and 10.4% Native American. A high correlation (adjusted R² = 0.65, p < 0.05) was observed between nine SNPs and quantitative skin pigmentation using multiple linear regression analysis. The correlations were notably smaller between skin pigmentation and biogeographic ancestry (adjusted R² = 0.45, p < 0.05), or markers in the leading forensic skin colour prediction system, the HIrisPlex-S (adjusted R² = 0.54, p < 0.05). Four of the nine SNPs, OCA2 rs1448484 (rank 2), APBA2 rs4424881 (rank 4), MFSD12 rs10424065 (rank 8), and TYRP1 1408799 (rank 9) were not investigated as part of the HIrisPlex-S selection process, and therefore not included in the HIrisPlex-S model. Our results indicate that these SNPs account for a substantial part of the skin colour variation in individuals of admixed ancestry. Hence, we suggest that these SNPs are considered when developing future skin colour prediction models.