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Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis
BACKGROUND: Left ventricular hypertrophy has multiple aetiologies including diabetes and genetic factors. We aimed to identify genetic variants predicting left ventricular hypertrophy in diabetic individuals. METHODS: Demographic, echocardiographic, prescribing, morbidity, mortality and genotyping d...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3729417/ https://www.ncbi.nlm.nih.gov/pubmed/23879873 http://dx.doi.org/10.1186/1475-2840-12-109 |
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author | Parry, Helen M Donnelly, Louise A Van Zuydam, Natalie Doney, Alexander SF Elder, Douglas HJ Morris, Andrew D Struthers, Alan D Palmer, Colin NA Lang, Chim C |
author_facet | Parry, Helen M Donnelly, Louise A Van Zuydam, Natalie Doney, Alexander SF Elder, Douglas HJ Morris, Andrew D Struthers, Alan D Palmer, Colin NA Lang, Chim C |
author_sort | Parry, Helen M |
collection | PubMed |
description | BACKGROUND: Left ventricular hypertrophy has multiple aetiologies including diabetes and genetic factors. We aimed to identify genetic variants predicting left ventricular hypertrophy in diabetic individuals. METHODS: Demographic, echocardiographic, prescribing, morbidity, mortality and genotyping databases connected with the Genetics of Diabetes Audit and Research in Tayside, Scotland project were accurately linked using a patient-specific identifier. Left ventricular hypertrophy cases were identified using echocardiographic data. Genotyping data from 973 cases and 1443 non-left ventricular hypertrophy controls were analysed, investigating whether single nucleotide polymorphisms associated with left ventricular hypertrophy in previous Genome Wide Association Studies predicted left ventricular hypertrophy in our population of individuals with type 2 diabetes. Meta-analysis assessed overall significance of these single nucleotide polymorphisms, which were also used to create gene scores. Logistic regression assessed whether these scores predicted left ventricular hypertrophy. RESULTS: Two single nucleotide polymorphisms previously associated with left ventricular hypertrophy were significant: rs17132261: OR 2.03, 95% CI 1.10-3.73, p-value 0.02 and rs2292462: OR 0.82, 95% CI 0.73-0.93 and p-value 2.26x10(-3). Meta-analysis confirmed rs17132261 and rs2292462 were associated with left ventricular hypertrophy (p=1.03x10(-8) and p=5.86x10(-10) respectively) and one single nucleotide polymorphisms in IGF1R (rs4966014) became genome wide significant upon meta-analysis although was not significant in our study. Gene scoring based on published single nucleotide polymorphisms also predicted left ventricular hypertrophy in our study. Rs17132261, within SLC25A46, encodes a mitochondrial phosphate transporter, implying abnormal myocardial energetics contribute to left ventricular hypertrophy development. Rs2292462 lies within the obesity-implicated neuromedin B gene. Rs4966014 lies within the IGF1R1 gene. IGF1 signalling is an established factor in cardiac hypertrophy. CONCLUSIONS: We created a resource to study genetics of left ventricular hypertrophy in diabetes and validated our left ventricular hypertrophy phenotype in replicating single nucleotide polymorphisms identified by previous genome wide association studies investigating left ventricular hypertrophy. |
format | Online Article Text |
id | pubmed-3729417 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37294172013-08-01 Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis Parry, Helen M Donnelly, Louise A Van Zuydam, Natalie Doney, Alexander SF Elder, Douglas HJ Morris, Andrew D Struthers, Alan D Palmer, Colin NA Lang, Chim C Cardiovasc Diabetol Original Investigation BACKGROUND: Left ventricular hypertrophy has multiple aetiologies including diabetes and genetic factors. We aimed to identify genetic variants predicting left ventricular hypertrophy in diabetic individuals. METHODS: Demographic, echocardiographic, prescribing, morbidity, mortality and genotyping databases connected with the Genetics of Diabetes Audit and Research in Tayside, Scotland project were accurately linked using a patient-specific identifier. Left ventricular hypertrophy cases were identified using echocardiographic data. Genotyping data from 973 cases and 1443 non-left ventricular hypertrophy controls were analysed, investigating whether single nucleotide polymorphisms associated with left ventricular hypertrophy in previous Genome Wide Association Studies predicted left ventricular hypertrophy in our population of individuals with type 2 diabetes. Meta-analysis assessed overall significance of these single nucleotide polymorphisms, which were also used to create gene scores. Logistic regression assessed whether these scores predicted left ventricular hypertrophy. RESULTS: Two single nucleotide polymorphisms previously associated with left ventricular hypertrophy were significant: rs17132261: OR 2.03, 95% CI 1.10-3.73, p-value 0.02 and rs2292462: OR 0.82, 95% CI 0.73-0.93 and p-value 2.26x10(-3). Meta-analysis confirmed rs17132261 and rs2292462 were associated with left ventricular hypertrophy (p=1.03x10(-8) and p=5.86x10(-10) respectively) and one single nucleotide polymorphisms in IGF1R (rs4966014) became genome wide significant upon meta-analysis although was not significant in our study. Gene scoring based on published single nucleotide polymorphisms also predicted left ventricular hypertrophy in our study. Rs17132261, within SLC25A46, encodes a mitochondrial phosphate transporter, implying abnormal myocardial energetics contribute to left ventricular hypertrophy development. Rs2292462 lies within the obesity-implicated neuromedin B gene. Rs4966014 lies within the IGF1R1 gene. IGF1 signalling is an established factor in cardiac hypertrophy. CONCLUSIONS: We created a resource to study genetics of left ventricular hypertrophy in diabetes and validated our left ventricular hypertrophy phenotype in replicating single nucleotide polymorphisms identified by previous genome wide association studies investigating left ventricular hypertrophy. BioMed Central 2013-07-23 /pmc/articles/PMC3729417/ /pubmed/23879873 http://dx.doi.org/10.1186/1475-2840-12-109 Text en Copyright © 2013 Parry et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Investigation Parry, Helen M Donnelly, Louise A Van Zuydam, Natalie Doney, Alexander SF Elder, Douglas HJ Morris, Andrew D Struthers, Alan D Palmer, Colin NA Lang, Chim C Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis |
title | Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis |
title_full | Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis |
title_fullStr | Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis |
title_full_unstemmed | Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis |
title_short | Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis |
title_sort | genetic variants predicting left ventricular hypertrophy in a diabetic population: a go-darts study including meta-analysis |
topic | Original Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3729417/ https://www.ncbi.nlm.nih.gov/pubmed/23879873 http://dx.doi.org/10.1186/1475-2840-12-109 |
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