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Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors

Epidemiology seeks to determine the causal effects of exposures on outcomes related to the health and wellbeing of populations. Observational studies, one of the most commonly used designs in epidemiology, can be biased due to confounding and reverse causation, which makes it difficult to establish...

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Detalles Bibliográficos
Autores principales: Bonilla, Carolina, Novaes Baccarini, Lara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7288659/
https://www.ncbi.nlm.nih.gov/pubmed/32375401
http://dx.doi.org/10.3390/genes11050507
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author Bonilla, Carolina
Novaes Baccarini, Lara
author_facet Bonilla, Carolina
Novaes Baccarini, Lara
author_sort Bonilla, Carolina
collection PubMed
description Epidemiology seeks to determine the causal effects of exposures on outcomes related to the health and wellbeing of populations. Observational studies, one of the most commonly used designs in epidemiology, can be biased due to confounding and reverse causation, which makes it difficult to establish causal relationships. In recent times, genetically informed methods, like Mendelian randomization (MR), have been developed in an attempt to overcome these disadvantages. MR relies on the association of genetic variants with outcomes of interest, where the genetic variants are proxies or instruments for modifiable exposures. Because genotypes are sorted independently and at random at the time of conception, they are less prone to confounding and reverse causation. Implementation of MR depends on, among other things, a strong association of the genetic variants with the exposure, which has usually been defined via genome-wide association studies (GWAS). Because GWAS have been most often carried out in European populations, the limited identification of strong instruments in other populations poses a major problem for the application of MR in Latin America. We suggest potential solutions that can be realized with the resources at hand and others that will have to wait for increased funding and access to technology.
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spelling pubmed-72886592020-06-17 Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors Bonilla, Carolina Novaes Baccarini, Lara Genes (Basel) Article Epidemiology seeks to determine the causal effects of exposures on outcomes related to the health and wellbeing of populations. Observational studies, one of the most commonly used designs in epidemiology, can be biased due to confounding and reverse causation, which makes it difficult to establish causal relationships. In recent times, genetically informed methods, like Mendelian randomization (MR), have been developed in an attempt to overcome these disadvantages. MR relies on the association of genetic variants with outcomes of interest, where the genetic variants are proxies or instruments for modifiable exposures. Because genotypes are sorted independently and at random at the time of conception, they are less prone to confounding and reverse causation. Implementation of MR depends on, among other things, a strong association of the genetic variants with the exposure, which has usually been defined via genome-wide association studies (GWAS). Because GWAS have been most often carried out in European populations, the limited identification of strong instruments in other populations poses a major problem for the application of MR in Latin America. We suggest potential solutions that can be realized with the resources at hand and others that will have to wait for increased funding and access to technology. MDPI 2020-05-04 /pmc/articles/PMC7288659/ /pubmed/32375401 http://dx.doi.org/10.3390/genes11050507 Text en © 2020 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
Bonilla, Carolina
Novaes Baccarini, Lara
Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors
title Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors
title_full Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors
title_fullStr Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors
title_full_unstemmed Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors
title_short Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors
title_sort genetic epidemiology in latin america: identifying strong genetic proxies for complex disease risk factors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7288659/
https://www.ncbi.nlm.nih.gov/pubmed/32375401
http://dx.doi.org/10.3390/genes11050507
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