Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil

Detalhes bibliográficos
Autor(a) principal: Souza, Juliana Maria de
Data de Publicação: 2021
Outros Autores: Bastos, Michael Lopes, Silva, Bárbara de Oliveira, Lima, Karla Giselle Gomes de, Albuquerque, Giwellington Silva de, Oliveira, Renata Santos de, Lima, Luísa Priscilla Oliveira de, Dellalibera, Edileine, Lins , Anthony José da Cunha Carneiro, Muniz, Maria Tereza Cartaxo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/20955
Resumo: The study of Externally Visible Characteristics (EVC) of pigmentation associated with SNPs (Single Nucleotide Polymorphisms) has become a target in the forensic field due to the possibility of phenotypically characterizing an individual. In Brazil, there are few data that shows the evaluation of some these markers, so further studies are necessary to understand better the pigmentation process related to genetic markers. The aim of this study was to test the association between 8 SNPs  present in HIrisplex tool and EVC to provide a starting point for the development of prediction models for heterogeneous populations like the one in Pernambuco. Were evaluated 176 individuals by associations between self-reported eye, hair and skin color data and polymorphisms. Artificial intelligence tools were used for the prediction models. Significant associations were found between rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) and rs1426654 (SLC24A5) with (EVC). The prediction models evaluated showed satisfactory prediction rates, rates above 60% for skin color and above 70% for eyes and hair. The associations found in our data show the importance of SNPs evaluation used in DNA Phenotyping, because of its ability to provide new information in the context of criminal investigations. Our data indicate that is possible to use molecular information to predict phenotypes in miscigenated populations, like the Brazilian population. These polymorphisms could be possible phenotypic predictors for the Pernambuco population.
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spelling Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil Fenotipado de DNA Forense: un punto de partida para el modelo de predicción de población de Pernambuco, BrasilFenotipagem por DNA Forense: um ponto de partida para o modelo de predição na população de Pernambuco, BrasilGenes de pigmentaçãoPopulação miscigenadaBrasilSNPsPreditores fenotípicosInteligência artificial.Pigmentation genesMiscigenated PopulationBrazilSNPsPhenotypic predictionArtificial intelligence.Genes de pigmentaciónPoblación mixtaBrasilSNPPredictores fenotípicosInteligencia artificial.The study of Externally Visible Characteristics (EVC) of pigmentation associated with SNPs (Single Nucleotide Polymorphisms) has become a target in the forensic field due to the possibility of phenotypically characterizing an individual. In Brazil, there are few data that shows the evaluation of some these markers, so further studies are necessary to understand better the pigmentation process related to genetic markers. The aim of this study was to test the association between 8 SNPs  present in HIrisplex tool and EVC to provide a starting point for the development of prediction models for heterogeneous populations like the one in Pernambuco. Were evaluated 176 individuals by associations between self-reported eye, hair and skin color data and polymorphisms. Artificial intelligence tools were used for the prediction models. Significant associations were found between rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) and rs1426654 (SLC24A5) with (EVC). The prediction models evaluated showed satisfactory prediction rates, rates above 60% for skin color and above 70% for eyes and hair. The associations found in our data show the importance of SNPs evaluation used in DNA Phenotyping, because of its ability to provide new information in the context of criminal investigations. Our data indicate that is possible to use molecular information to predict phenotypes in miscigenated populations, like the Brazilian population. These polymorphisms could be possible phenotypic predictors for the Pernambuco population.El estudio de las Características Externamente Visibles (CEV) de la pigmentación asociada a los SNP (Single Nucleotide Polymorphisms) se ha convertido en un objetivo en el área forense debido a la posibilidad de caracterizar fenotípicamente a un individuo. En Brasil, hay pocos datos que muestren la evaluación de algunos de estos marcadores, por lo que se necesitan más estudios para comprender mejor el proceso de pigmentación relacionado con los marcadores genéticos. El objetivo de este estudio fue probar la asociación entre 8 SNP presentes en la herramienta HIrisplex y el CEV para proporcionar un punto de partida para el desarrollo de modelos de predicción para poblaciones heterogéneas como la de Pernambuco. Se evaluaron 176 individuos a través de asociaciones entre los datos autoinformados sobre el color de ojos, cabello y piel y polimorfismos. Se utilizaron herramientas de inteligencia artificial para los modelos de predicción. Se encontraron asociaciones significativas entre rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) y rs1426654 (SLC24A5) con CEV. Los modelos de predicción evaluados presentaron tasas de predicción satisfactorias, superiores al 60% para el color de piel y superiores al 70% para ojos y cabello. Las asociaciones encontradas en nuestros datos muestran la importancia de evaluar los SNP utilizados en el fenotipado de DNA, debido a su capacidad para aportar nueva información en el contexto de las investigaciones penales. Nuestros datos indican que es posible utilizar información molecular para predecir fenotipos en poblaciones mixtas, como la brasileña. Estos polimorfismos pueden ser posibles predictores fenotípicos para la población de Pernambuco.O estudo das Características Externamente Visíveis (CEV) da pigmentação associada a SNPs (Single Nucleotide Polymorphisms) tornou-se um alvo na área forense devido à possibilidade de caracterizar fenotipicamente um indivíduo. No Brasil, poucos são os dados que mostram a avaliação de alguns desses marcadores, portanto, mais estudos são necessários para entender melhor o processo de pigmentação relacionado aos marcadores genéticos. O objetivo deste estudo foi testar a associação entre 8 SNPs presentes na ferramenta HIrisplex e as CEV para fornecer um ponto de partida para o desenvolvimento de modelos de predição para populações heterogêneas como a de Pernambuco. 176 indivíduos foram avaliados por meio de associações entre dados autorreferidos de cor dos olhos, cabelo e pele e os polimorfismos. Ferramentas de inteligência artificial foram utilizadas para os modelos de predição. Foram encontradas associações significativas entre rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) e rs1426654 (SLC24A5) com as CEV. Os modelos de predição avaliados apresentaram índices de predição satisfatórios, acima de 60% para cor da pele e acima de 70% para olhos e cabelos. As associações encontradas em nossos dados mostram a importância da avaliação de SNPs utilizados na Fenotipagem por DNA, por sua capacidade de fornecer novas informações no contexto de investigações criminais. Os dados encontrados indicam que é possível usar informações moleculares para predizer fenótipos em populações miscigenadas, como a brasileira. Esses polimorfismos podem ser possíveis preditores fenotípicos para a população de Pernambuco.Research, Society and Development2021-10-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2095510.33448/rsd-v10i13.20955Research, Society and Development; Vol. 10 No. 13; e262101320955Research, Society and Development; Vol. 10 Núm. 13; e262101320955Research, Society and Development; v. 10 n. 13; e2621013209552525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/20955/18898Copyright (c) 2021 Juliana Maria de Souza; Michael Lopes Bastos; Bárbara de Oliveira Silva; Karla Giselle Gomes de Lima; Giwellington Silva de Albuquerque; Renata Santos de Oliveira; Luísa Priscilla Oliveira de Lima; Edileine Dellalibera; Anthony José da Cunha Carneiro Lins ; Maria Tereza Cartaxo Munizhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSouza, Juliana Maria de Bastos, Michael LopesSilva, Bárbara de OliveiraLima, Karla Giselle Gomes deAlbuquerque, Giwellington Silva de Oliveira, Renata Santos de Lima, Luísa Priscilla Oliveira deDellalibera, Edileine Lins , Anthony José da Cunha CarneiroMuniz, Maria Tereza Cartaxo 2021-11-21T18:26:28Zoai:ojs.pkp.sfu.ca:article/20955Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:40:28.569100Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
Fenotipado de DNA Forense: un punto de partida para el modelo de predicción de población de Pernambuco, Brasil
Fenotipagem por DNA Forense: um ponto de partida para o modelo de predição na população de Pernambuco, Brasil
title Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
spellingShingle Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
Souza, Juliana Maria de
Genes de pigmentação
População miscigenada
Brasil
SNPs
Preditores fenotípicos
Inteligência artificial.
Pigmentation genes
Miscigenated Population
Brazil
SNPs
Phenotypic prediction
Artificial intelligence.
Genes de pigmentación
Población mixta
Brasil
SNP
Predictores fenotípicos
Inteligencia artificial.
title_short Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
title_full Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
title_fullStr Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
title_full_unstemmed Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
title_sort Forensic DNA Phenotyping: starting point to prediction model in Pernambuco population, Brazil
author Souza, Juliana Maria de
author_facet Souza, Juliana Maria de
Bastos, Michael Lopes
Silva, Bárbara de Oliveira
Lima, Karla Giselle Gomes de
Albuquerque, Giwellington Silva de
Oliveira, Renata Santos de
Lima, Luísa Priscilla Oliveira de
Dellalibera, Edileine
Lins , Anthony José da Cunha Carneiro
Muniz, Maria Tereza Cartaxo
author_role author
author2 Bastos, Michael Lopes
Silva, Bárbara de Oliveira
Lima, Karla Giselle Gomes de
Albuquerque, Giwellington Silva de
Oliveira, Renata Santos de
Lima, Luísa Priscilla Oliveira de
Dellalibera, Edileine
Lins , Anthony José da Cunha Carneiro
Muniz, Maria Tereza Cartaxo
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Souza, Juliana Maria de
Bastos, Michael Lopes
Silva, Bárbara de Oliveira
Lima, Karla Giselle Gomes de
Albuquerque, Giwellington Silva de
Oliveira, Renata Santos de
Lima, Luísa Priscilla Oliveira de
Dellalibera, Edileine
Lins , Anthony José da Cunha Carneiro
Muniz, Maria Tereza Cartaxo
dc.subject.por.fl_str_mv Genes de pigmentação
População miscigenada
Brasil
SNPs
Preditores fenotípicos
Inteligência artificial.
Pigmentation genes
Miscigenated Population
Brazil
SNPs
Phenotypic prediction
Artificial intelligence.
Genes de pigmentación
Población mixta
Brasil
SNP
Predictores fenotípicos
Inteligencia artificial.
topic Genes de pigmentação
População miscigenada
Brasil
SNPs
Preditores fenotípicos
Inteligência artificial.
Pigmentation genes
Miscigenated Population
Brazil
SNPs
Phenotypic prediction
Artificial intelligence.
Genes de pigmentación
Población mixta
Brasil
SNP
Predictores fenotípicos
Inteligencia artificial.
description The study of Externally Visible Characteristics (EVC) of pigmentation associated with SNPs (Single Nucleotide Polymorphisms) has become a target in the forensic field due to the possibility of phenotypically characterizing an individual. In Brazil, there are few data that shows the evaluation of some these markers, so further studies are necessary to understand better the pigmentation process related to genetic markers. The aim of this study was to test the association between 8 SNPs  present in HIrisplex tool and EVC to provide a starting point for the development of prediction models for heterogeneous populations like the one in Pernambuco. Were evaluated 176 individuals by associations between self-reported eye, hair and skin color data and polymorphisms. Artificial intelligence tools were used for the prediction models. Significant associations were found between rs1800404 (OCA2), rs6058017 (ASIP), rs16891982 (SLC45A2) and rs1426654 (SLC24A5) with (EVC). The prediction models evaluated showed satisfactory prediction rates, rates above 60% for skin color and above 70% for eyes and hair. The associations found in our data show the importance of SNPs evaluation used in DNA Phenotyping, because of its ability to provide new information in the context of criminal investigations. Our data indicate that is possible to use molecular information to predict phenotypes in miscigenated populations, like the Brazilian population. These polymorphisms could be possible phenotypic predictors for the Pernambuco population.
publishDate 2021
dc.date.none.fl_str_mv 2021-10-11
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/20955
10.33448/rsd-v10i13.20955
url https://rsdjournal.org/index.php/rsd/article/view/20955
identifier_str_mv 10.33448/rsd-v10i13.20955
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/20955/18898
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 10 No. 13; e262101320955
Research, Society and Development; Vol. 10 Núm. 13; e262101320955
Research, Society and Development; v. 10 n. 13; e262101320955
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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