Gender is a major factor explaining discrepancies in eye colour prediction based on HERC2/OCA2 genotype and the IrisPlex model

Martínez-Cadenas, Conrado; Peña‐Chilet, María; Ibarrola‐Villava, Maider; Ribas, Gloría

doi:10.1016/j.fsigen.2013.03.007

Cited by 42 publications

(65 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Similar results were observed for already published male and female eye colour frequency data in Icelandic and Dutch populations [8] but not in Australian [9] and Polish populations [10]. Martinez-Cadenas and co-workers [1] suggested that the prediction success of the IrisPlex model and other models used to predict eye colour phenotypes from DNA genotypes may be improved by including gender as a factor. As a reply to Martinez-Cadenas and coworker [3], the inventors of the IrisPlex assay tested whether the prediction of categorical eye colour (blue, intermediate and brown) was improved when gender was considered [3].…”

Section: Introductionsupporting

confidence: 87%

“…Our effect was predicted using an Italian population collected in We are aware of the fact that the number of individuals studied was relatively small and limited to only one population. However, the results presented here and by Martinez-Cadenas and co-workers [1,2] support a population specific gender effect on eye colour. To fully explore possible population specific effects, more populations need to be studied.…”

Section: Discussionsupporting

confidence: 49%

“…Thus, the results presented here and by Martinez-Cadenas and co-workers [1,2] were unexpected. It raises the question whether the gender effect is, although statistically significant in Spanish and Italian population sample sets, relevant for forensic genetic case work in specific populations.…”

Section: Accuracy Of the Irisplex Prediction Model In The Italian Popcontrasting

confidence: 50%

“…The IrisPlex assay predicts blue and brown eye colours with high accuracy but predict the intermediate eye colours with lower accuracy [4]. Two recent studies [1,2] suggested that gender is contributing to human eye colour variation. Males were found to be more likely to have blue eye colour compared to females, whereas females showed higher frequencies of intermediate and brown…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model

Pietroni

Andersen

Johansen

et al. 2014

Forensic Science International: Genetics

View full text Add to dashboard Cite

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. In this study, we investigate the role of gender as a factor that contributes to eye colour variation and suggest that the gender effect on eye colour is population specific.A total of 230 Italian individuals were typed for the six IrisPlex SNPs (rs12913832, rs1800407, rs12896399, rs1393350, rs16891982 and rs12203592). A quantitative eye colour score (Pixel Index of the Eye: PIE-score) was calculated based on digital eye images using the custom made DIAT software. The results were compared with those of Danish and Swedish population samples.As expected, we found HERC2 rs12913832 as the main predictor of human eye colour independently of ancestry. Furthermore, we found gender to be significantly associated with quantitative eye colour measurements in the Italian population sample. We found that the association was statistically significant only among Italian individuals typed as heterozygote GA for HERC2 rs12913832. Interestingly, we did not observe the same association in the Danish and Swedish population. This indicated that the gender effect on eye colour is population specific. We estimated the effect of gender on quantitative eye colour in the Italian population sample to be 4.9%. Among gender and the IrisPlex SNPs, gender ranked as the second most important predictor of human eye colour variation in Italians after HERC2 rs12913832. We, furthermore, tested the five lower ranked IrisPlex predictors, and evaluated all possible 3 6 (729) genotype combinations of the IrisPlex assay and their corresponding predictive values using the IrisPlex prediction model [4]. The results suggested that maximum three (rs12913832, rs1800407, rs16891982) of the six IrisPlex SNPs are useful in practical forensic genetic casework.

show abstract

Section: Introductionsupporting

confidence: 87%

Section: Discussionsupporting

confidence: 49%

Section: Accuracy Of the Irisplex Prediction Model In The Italian Popcontrasting

confidence: 50%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model

Pietroni

Andersen

Johansen

et al. 2014

Forensic Science International: Genetics

View full text Add to dashboard Cite

show abstract

“…Recent studies point to Caucasian females having slightly darker eye colour (162,163) and skin colour (25) than Caucasian males. Regarding melanoma, females show lower melanoma predisposition and incidence, lower risk of metastases and longer melanoma-specific survival rates than males (130,131).…”

Section: Introductionmentioning

confidence: 99%

The genetic basis of sunlight sensitivity and melanoma-risk pigmentation phenotypes: The role of sex-specific genetic effects, 3' untranslated regions and melanoma susceptibility genes

Fuster¹

View full text Add to dashboard Cite

AGRADECIMIENTOSAntes de presentar este trabajo, es momento de agradecer el respaldo de todas aquellas personas que han hecho posible que hoy sea una finisher de esta carrera de larga distancia que es hacer una tesis doctoral.Mis primeras líneas de agradecimiento son para mi director, Conrado Martínez-Cadenas, y co-directora de tesis, Gloria Ribas; quienes con su dedicación, experiencia y profesionalidad me han guiado de manera excepcional durante las diferentes fases de este trabajo, tanto en el proceso puramente experimental como en el análisis, interpretación y presentación de los datos. A Conrado, gracias por darme la oportunidad de realizar la tesis en su grupo de investigación, además de por su apoyo personal, confianza, cercanía y dedicación. Gracias por mover cielo y tierra porque esto fuera posible. A Gloria, gracias por abrirme las puertas de su laboratorio y, sobre todo, por sus excepcionales consejos que, no sólo me han ayudado a desarrollar esta tesis, sino que también han permitido la publicación de los resultados obtenidos.Gracias a Maider Ibarrola-Villava y Maria Peña-Chilet, miembros del grupo de investigación del Departamento de Oncología del INCLIVA, por acompañarme en este largo camino, por su valiosa aportación y su gran compañerismo.Gracias a Zalfa Abdel-Malek por acogerme en su laboratorio y darme la oportunidad de participar en un ambicioso proyecto que ha enriquecido sustancialmente mi carrera investigadora. Gracias por su exigencia y crítica constructiva, pero también por su cariño durante mi estancia. Mención especial a Vicky Sope y Renny Starner por su incalculable ayuda, paciencia y amistad. Gracias de corazón por dejarme empapar de vuestra profesionalidad.Gracias a todo el personal de la Unidad Predepartamental de Medicina de la Universitat Jaume I de Castellón, por el buen humor y compañerismo demostrado. Mención especial para mis compañeros de batalla en el laboratorio. Gracias por esas largas conversaciones y hacerme sentir afortunada por compartir mi trabajo diario con vosotros. Gracias por todo lo compartido.Gracias también a todas esas personas anónimas que voluntariamente han donado una muestra, y al personal médico de los diferentes hospitales encargados de recoger dichas muestras, ya que sin su contribución este trabajo no habría existido.Finalmente, es necesario expresar mi mayor gratitud a todas esas personas que indirectamente también han sido partícipes de este trabajo. A mi familia, por creer en mí.A mi padre, por enseñarme el valor del esfuerzo, el trabajo duro y la disciplina. A mi madre, por enseñarme a tener paciencia. A mi hermana, por ser mi mejor amiga y consejera, especialmente en la estadística y el uso del R. A Manoli, porque todo lo vivido juntas es lo que me ha hecho ser lo que soy. A mi grupo de entrenamiento, por ayudarme a evadirme de todo en los momentos que más lo necesitaba. A Iván, por estar siempre a mi lado. Por no dejarme caer. Por saber cómo hacer que confiara en mi misma. Por hacerme ver que soy una privilegiada hasta en los momentos menos buenos...

show abstract

Contributions byMC1RVariants to Melanoma Risk in Males and Females

et al. 2018

View full text Add to dashboard Cite

revious studies have shown population-specific differences in pigmentation phenotype between males and females regarding phototype, tanning ability, and eye color. [1][2][3][4][5] Recently, a Spanish group described a stronger effect of melanocortin-1-receptor (MC1R) variants on skin phototype in females compared with males 6 : in females, MC1R variants were associated with lower phototypes compared with male carriers of the same variants. This finding is of interest because MC1R is known to be highly polymorphic-with more than 80 variants described-and is the main regulator of pigmentation phenotype, including hair color, skin pigmentation, and sun sensitivity at the same time. [7][8][9][10] Activation and subsequent signaling of this G-protein coupled receptor result in 2 different types of melanin: the lighter, yellowreddish pheomelanin and the darker, brown to black eumelanin. The ratio of eumelanin and pheomelanin is determined by the variants an individual carries and results in particular phenotypes. Variants that were found to be associated with red hair and fair skin were classified as "R" (high-risk) and "r" (lowrisk) variants. These variants also have been well described as being associated with melanoma risk, which is plausible owing to less effective protection of pheomelanin against UV radiation 7,8,10-12 as well as pro-oxidant properties. Only recently, MC1R red hair variants were associated with melanoma, even independent of sun exposure. 13 Differences between the sexes do not affect only skin pigmentation. There are also differences in age at onset, incidence rates, site of tumor occurrence, and survival between male and female patients with melanoma. [14][15][16][17][18][19] Despite these well-acknowledged differences, an explanation for those differences is still missing. It thus seems of particular interest to elucidate the role of genetic risk factors (eg, MC1R) and melanoma risk in males and females separately to better understand possible underlying sex-dependent differences in mela-IMPORTANCE Recently, the red hair variants of MC1R were found to contribute differently to pigmentation phenotype in males and females.OBJECTIVE To investigate the role of these variants in melanoma risk in males and females separately because carriers of the red hair variants of MC1R are at increased risk of melanoma. DESIGN, SETTING, AND PARTICIPANTSIn this hospital-based, case-control study, we evaluated the effect of MC1R and melanoma risk for males and females separately by performing multivariate logistic regression analyses. MAIN OUTCOMES AND MEASURES Association of MC1R variants and melanoma risk in males and females.RESULTS A total of 905 females (473 melanoma cases, 432 controls) and 886 males (518 melanoma cases, 368 controls) were included in the analyses. The mean (SD) age of the study population was 59.2 (15.6). In females, carrying any MC1R red hair variants remained an independent risk factor of melanoma in a multivariable analysis (adjusted odds ratio [OR], 2.19 [95% CI, 1.60-2.99]), whereas in...

show abstract

Gender is a major factor explaining discrepancies in eye colour prediction based on HERC2/OCA2 genotype and the IrisPlex model

Cited by 42 publications

References 28 publications

The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model

The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model

The genetic basis of sunlight sensitivity and melanoma-risk pigmentation phenotypes: The role of sex-specific genetic effects, 3' untranslated regions and melanoma susceptibility genes

Contributions byMC1RVariants to Melanoma Risk in Males and Females

Contact Info

Product

Resources

About