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Genome-wide association studies with metabolomics
Genome-wide association studies (GWAS) analyze the genetic component of a phenotype or the etiology of a disease. Despite the success of many GWAS, little progress has been made in uncovering the underlying mechanisms for many diseases. The use of metabolomics as a readout of molecular phenotypes ha...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3446262/ https://www.ncbi.nlm.nih.gov/pubmed/22546499 http://dx.doi.org/10.1186/gm333 |
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author | Adamski, Jerzy |
author_facet | Adamski, Jerzy |
author_sort | Adamski, Jerzy |
collection | PubMed |
description | Genome-wide association studies (GWAS) analyze the genetic component of a phenotype or the etiology of a disease. Despite the success of many GWAS, little progress has been made in uncovering the underlying mechanisms for many diseases. The use of metabolomics as a readout of molecular phenotypes has enabled the discovery of previously undetected associations between diseases and signaling and metabolic pathways. In addition, combining GWAS and metabolomic information allows the simultaneous analysis of the genetic and environmental impacts on homeostasis. Most success has been seen in metabolic diseases such as diabetes, obesity and dyslipidemia. Recently, associations between loci such as FADS1, ELOVL2 or SLC16A9 and lipid concentrations have been explained by GWAS with metabolomics. Combining GWAS with metabolomics (mGWAS) provides the robust and quantitative information required for the development of specific diagnostics and targeted drugs. This review discusses the limitations of GWAS and presents examples of how metabolomics can overcome these limitations with the focus on metabolic diseases. |
format | Online Article Text |
id | pubmed-3446262 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34462622013-04-30 Genome-wide association studies with metabolomics Adamski, Jerzy Genome Med Review Genome-wide association studies (GWAS) analyze the genetic component of a phenotype or the etiology of a disease. Despite the success of many GWAS, little progress has been made in uncovering the underlying mechanisms for many diseases. The use of metabolomics as a readout of molecular phenotypes has enabled the discovery of previously undetected associations between diseases and signaling and metabolic pathways. In addition, combining GWAS and metabolomic information allows the simultaneous analysis of the genetic and environmental impacts on homeostasis. Most success has been seen in metabolic diseases such as diabetes, obesity and dyslipidemia. Recently, associations between loci such as FADS1, ELOVL2 or SLC16A9 and lipid concentrations have been explained by GWAS with metabolomics. Combining GWAS with metabolomics (mGWAS) provides the robust and quantitative information required for the development of specific diagnostics and targeted drugs. This review discusses the limitations of GWAS and presents examples of how metabolomics can overcome these limitations with the focus on metabolic diseases. BioMed Central 2012-04-30 /pmc/articles/PMC3446262/ /pubmed/22546499 http://dx.doi.org/10.1186/gm333 Text en Copyright ©2012 BioMed Central Ltd. |
spellingShingle | Review Adamski, Jerzy Genome-wide association studies with metabolomics |
title | Genome-wide association studies with metabolomics |
title_full | Genome-wide association studies with metabolomics |
title_fullStr | Genome-wide association studies with metabolomics |
title_full_unstemmed | Genome-wide association studies with metabolomics |
title_short | Genome-wide association studies with metabolomics |
title_sort | genome-wide association studies with metabolomics |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3446262/ https://www.ncbi.nlm.nih.gov/pubmed/22546499 http://dx.doi.org/10.1186/gm333 |
work_keys_str_mv | AT adamskijerzy genomewideassociationstudieswithmetabolomics |