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A Predictive Model Assessing Genetic Susceptibility Risk at Workplace

(1) Background: The study of susceptibility biomarkers in the immigrant workforce integrated into the social tissue of European host countries is always a challenge, due to high individual heterogeneity and the admixing of different ethnicities in the same workplace. These workers having distinct cu...

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Autores principales: Chiarella, Pieranna, Capone, Pasquale, Carbonari, Damiano, Sisto, Renata
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603935/
https://www.ncbi.nlm.nih.gov/pubmed/31195756
http://dx.doi.org/10.3390/ijerph16112012
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author Chiarella, Pieranna
Capone, Pasquale
Carbonari, Damiano
Sisto, Renata
author_facet Chiarella, Pieranna
Capone, Pasquale
Carbonari, Damiano
Sisto, Renata
author_sort Chiarella, Pieranna
collection PubMed
description (1) Background: The study of susceptibility biomarkers in the immigrant workforce integrated into the social tissue of European host countries is always a challenge, due to high individual heterogeneity and the admixing of different ethnicities in the same workplace. These workers having distinct cultural backgrounds, beliefs, diets, and habits, as well as a poor knowledge of the foreign language, may feel reluctant to donate their biological specimens for the biomonitoring research studies. (2) Methods: A model predicting ethnicity-specific susceptibility based on principal component analysis has been conceived, using the genotype frequency of the investigated populations available in publicly accessible databases. (3) Results: Correlations among ethnicities and between ethnic and polymorphic genes have been found, and low/high-risk profiles have been identified as valuable susceptibility biomarkers. (4) Conclusions: In the absence of workers’ consent or access to blood genotyping, ethnicity represents a good indicator of the subject’s genotype. This model, associating ethnicity-specific genotype frequency with the susceptibility biomarkers involved in the metabolism of toxicants, may replace genotyping, ensuring the necessary safety and health conditions of workers assigned to hazardous jobs.
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spelling pubmed-66039352019-07-19 A Predictive Model Assessing Genetic Susceptibility Risk at Workplace Chiarella, Pieranna Capone, Pasquale Carbonari, Damiano Sisto, Renata Int J Environ Res Public Health Article (1) Background: The study of susceptibility biomarkers in the immigrant workforce integrated into the social tissue of European host countries is always a challenge, due to high individual heterogeneity and the admixing of different ethnicities in the same workplace. These workers having distinct cultural backgrounds, beliefs, diets, and habits, as well as a poor knowledge of the foreign language, may feel reluctant to donate their biological specimens for the biomonitoring research studies. (2) Methods: A model predicting ethnicity-specific susceptibility based on principal component analysis has been conceived, using the genotype frequency of the investigated populations available in publicly accessible databases. (3) Results: Correlations among ethnicities and between ethnic and polymorphic genes have been found, and low/high-risk profiles have been identified as valuable susceptibility biomarkers. (4) Conclusions: In the absence of workers’ consent or access to blood genotyping, ethnicity represents a good indicator of the subject’s genotype. This model, associating ethnicity-specific genotype frequency with the susceptibility biomarkers involved in the metabolism of toxicants, may replace genotyping, ensuring the necessary safety and health conditions of workers assigned to hazardous jobs. MDPI 2019-06-05 2019-06 /pmc/articles/PMC6603935/ /pubmed/31195756 http://dx.doi.org/10.3390/ijerph16112012 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chiarella, Pieranna
Capone, Pasquale
Carbonari, Damiano
Sisto, Renata
A Predictive Model Assessing Genetic Susceptibility Risk at Workplace
title A Predictive Model Assessing Genetic Susceptibility Risk at Workplace
title_full A Predictive Model Assessing Genetic Susceptibility Risk at Workplace
title_fullStr A Predictive Model Assessing Genetic Susceptibility Risk at Workplace
title_full_unstemmed A Predictive Model Assessing Genetic Susceptibility Risk at Workplace
title_short A Predictive Model Assessing Genetic Susceptibility Risk at Workplace
title_sort predictive model assessing genetic susceptibility risk at workplace
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603935/
https://www.ncbi.nlm.nih.gov/pubmed/31195756
http://dx.doi.org/10.3390/ijerph16112012
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