The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial.
<h4>Objective</h4>To investigate the association of risk alleles for type 2 diabetes with prediabetes accounting for age, anthropometry, inflammatory markers and lifestyle habits.<h4>Design</h4>Cross-sectional study of 129 men and 157 women of medium-sized companies in northe...
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2013
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oai:doaj.org-article:b31f11e3e20a4f329e9f9a88ee95e35f2021-11-18T08:53:13ZThe association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial.1932-620310.1371/journal.pone.0075807https://doaj.org/article/b31f11e3e20a4f329e9f9a88ee95e35f2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24098730/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Objective</h4>To investigate the association of risk alleles for type 2 diabetes with prediabetes accounting for age, anthropometry, inflammatory markers and lifestyle habits.<h4>Design</h4>Cross-sectional study of 129 men and 157 women of medium-sized companies in northern Germany in the Delay of Impaired Glucose Tolerance by a Healthy Lifestyle Trial (DELIGHT).<h4>Methods</h4>Besides established risk factors, 41 single nucleotide polymorphisms (SNPs) that have previously been found to be associated with type 2 diabetes were analyzed. As a nonparametric test a random forest approach was used that allows processing of a large number of predictors. Variables with the highest impact were entered into a multivariate logistic regression model to estimate their association with prediabetes.<h4>Results</h4>Individuals with prediabetes were characterized by a slightly, but significantly higher number of type 2 diabetes risk alleles (42.5±4.1 vs. 41.3±4.1, p = 0.013). After adjustment for age and waist circumference 6 SNPs with the highest impact in the random forest analysis were associated with risk for prediabetes in a logistic regression model. At least 5 of these SNPs were positively related to prediabetic status (odds ratio for prediabetes 1.57 per allele (Cl 1.21-2.10, p = 0.001)).<h4>Conclusions</h4>This explorative analysis of data of DELIGHT demonstrates that at least 6 out of 41 genetic variants characteristic of individuals with type 2 diabetes may also be associated with prediabetes. Accumulation of these risk alleles may markedly increase the risk for prediabetes. However, prospective studies are required to corroborate these findings and to demonstrate the predictive value of these genetic variants for the risk to develop prediabetes.Birgit-Christiane ZyriaxRamona SalazarWolfgang HoeppnerEik VettorazziChristian HerderEberhard WindlerPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 9, p e75807 (2013) |
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Medicine R Science Q |
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Medicine R Science Q Birgit-Christiane Zyriax Ramona Salazar Wolfgang Hoeppner Eik Vettorazzi Christian Herder Eberhard Windler The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial. |
| description |
<h4>Objective</h4>To investigate the association of risk alleles for type 2 diabetes with prediabetes accounting for age, anthropometry, inflammatory markers and lifestyle habits.<h4>Design</h4>Cross-sectional study of 129 men and 157 women of medium-sized companies in northern Germany in the Delay of Impaired Glucose Tolerance by a Healthy Lifestyle Trial (DELIGHT).<h4>Methods</h4>Besides established risk factors, 41 single nucleotide polymorphisms (SNPs) that have previously been found to be associated with type 2 diabetes were analyzed. As a nonparametric test a random forest approach was used that allows processing of a large number of predictors. Variables with the highest impact were entered into a multivariate logistic regression model to estimate their association with prediabetes.<h4>Results</h4>Individuals with prediabetes were characterized by a slightly, but significantly higher number of type 2 diabetes risk alleles (42.5±4.1 vs. 41.3±4.1, p = 0.013). After adjustment for age and waist circumference 6 SNPs with the highest impact in the random forest analysis were associated with risk for prediabetes in a logistic regression model. At least 5 of these SNPs were positively related to prediabetic status (odds ratio for prediabetes 1.57 per allele (Cl 1.21-2.10, p = 0.001)).<h4>Conclusions</h4>This explorative analysis of data of DELIGHT demonstrates that at least 6 out of 41 genetic variants characteristic of individuals with type 2 diabetes may also be associated with prediabetes. Accumulation of these risk alleles may markedly increase the risk for prediabetes. However, prospective studies are required to corroborate these findings and to demonstrate the predictive value of these genetic variants for the risk to develop prediabetes. |
| format |
article |
| author |
Birgit-Christiane Zyriax Ramona Salazar Wolfgang Hoeppner Eik Vettorazzi Christian Herder Eberhard Windler |
| author_facet |
Birgit-Christiane Zyriax Ramona Salazar Wolfgang Hoeppner Eik Vettorazzi Christian Herder Eberhard Windler |
| author_sort |
Birgit-Christiane Zyriax |
| title |
The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial. |
| title_short |
The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial. |
| title_full |
The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial. |
| title_fullStr |
The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial. |
| title_full_unstemmed |
The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial. |
| title_sort |
association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2013 |
| url |
https://doaj.org/article/b31f11e3e20a4f329e9f9a88ee95e35f |
| work_keys_str_mv |
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