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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7288659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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