|Autorzy publikacji z podkreśleniem autorów z projektu BBMRI.pl||Kukla-Bartoszek M., Pośpiech E., Spólnicka M., Karłowska-Pik J., Strapagiel D., Żądzińska E., Rosset I., Sobalska-Kwapis M., Słomka M., Walsh S., Kayser M., Sitek A., Branicki W.|
|Nazwa czasopisma||Forensic Science International: Genetics|
|IF czasopisma w czasie publikacji pracy||4,884|
|Punkty MNiSW w czasie publikacji pracy||45|
|Streszczenie w j. angielskim lub krótki opis pracy||Predictive DNA analysis of externally visible characteristics exerts an increasing influence on contemporary forensic and anthropological investigations, with pigmentation traits currently being the most advanced for predictive modelling. Since pigmentation prediction error in some cases may be due to the result of age-related hair colour darkening, and sex influence in eye colour, this study aims to investigate these less explored phenomena on a group of juvenile individuals. Pigmentation phenotypes of children between the age of 6–13 years old were evaluated, in addition to data about their hair colour during early childhood from a select number of these individuals. The HIrisPlex models for DNA-based eye and hair colour prediction were used with input from SNP genotyping using massive parallel sequencing. Analysis of the total group of 476 children showed high accuracy in blue (AUC = 0.89) and brown (AUC = 0.91) eye colour prediction, while hair colour was predicted with AUC = 0.64 for blond, AUC = 0.64 for brown and AUC = 0.97 for red. 70.8% (n = 143) of the total number of children phenotypically blond for hair colour during early childhood progressed to brown during advanced childhood. In 70.6% (n = 101) of those cases, an incorrect blond hair prediction was made during the time of analysis. A noticeable decline in AUC values for blond (from 0.76 to 0.65) and brown (from 0.72 to 0.64) were observed when comparing hair colour prediction outcomes for the phenotypes recorded for the two different time points (at the age of 2–3 and 6–13). The number of incorrect blond hair colour predictions was significantly higher in children with brown hair at age 6–13 who were blond at early childhood (n = 47, 32.9%), relative to children who had brown hair at both time points (n = 6, 9.4%). However, in 28.0% (n = 40) of children who did experience hair colour darkening, HIrisPlex provided the correct prediction for the darkened hair colour phenotype, despite them being blond in early childhood. Our study implies that HIrisPlex can correctly predict adult hair colour in some individuals who experience age-related hair colour darkening during adolescence. However, in most instances prediction seems to default to the pre-adolescent hair colour for individuals with this phenomenon. In the future, the full adolescent age range in which hair colour darkening can occur should be considered in the study samples used for training hair colour prediction models to obtain a more complete picture of the phenomenon and its impact on DNA-based hair colour prediction in adults.
|Link do publikacji||Investigating the impact of age depended hair colour darkening during childhood on DNA-based hair colour prediction with the HIrisPlex system
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