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Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population
Variants in HNF1A encoding hepatocyte nuclear factor 1α (HNF-1A) are associated with maturity-onset diabetes of the young form 3 (MODY 3) and type 2 diabetes. We investigated whether functional classification of HNF1A rare coding variants can inform models of diabetes risk prediction in the general...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Diabetes Association
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860263/ https://www.ncbi.nlm.nih.gov/pubmed/27899486 http://dx.doi.org/10.2337/db16-0460 |
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author | Najmi, Laeya Abdoli Aukrust, Ingvild Flannick, Jason Molnes, Janne Burtt, Noel Molven, Anders Groop, Leif Altshuler, David Johansson, Stefan Bjørkhaug, Lise Njølstad, Pål Rasmus |
author_facet | Najmi, Laeya Abdoli Aukrust, Ingvild Flannick, Jason Molnes, Janne Burtt, Noel Molven, Anders Groop, Leif Altshuler, David Johansson, Stefan Bjørkhaug, Lise Njølstad, Pål Rasmus |
author_sort | Najmi, Laeya Abdoli |
collection | PubMed |
description | Variants in HNF1A encoding hepatocyte nuclear factor 1α (HNF-1A) are associated with maturity-onset diabetes of the young form 3 (MODY 3) and type 2 diabetes. We investigated whether functional classification of HNF1A rare coding variants can inform models of diabetes risk prediction in the general population by analyzing the effect of 27 HNF1A variants identified in well-phenotyped populations (n = 4,115). Bioinformatics tools classified 11 variants as likely pathogenic and showed no association with diabetes risk (combined minor allele frequency [MAF] 0.22%; odds ratio [OR] 2.02; 95% CI 0.73–5.60; P = 0.18). However, a different set of 11 variants that reduced HNF-1A transcriptional activity to <60% of normal (wild-type) activity was strongly associated with diabetes in the general population (combined MAF 0.22%; OR 5.04; 95% CI 1.99–12.80; P = 0.0007). Our functional investigations indicate that 0.44% of the population carry HNF1A variants that result in a substantially increased risk for developing diabetes. These results suggest that functional characterization of variants within MODY genes may overcome the limitations of bioinformatics tools for the purposes of presymptomatic diabetes risk prediction in the general population. |
format | Online Article Text |
id | pubmed-5860263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | American Diabetes Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-58602632018-03-21 Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population Najmi, Laeya Abdoli Aukrust, Ingvild Flannick, Jason Molnes, Janne Burtt, Noel Molven, Anders Groop, Leif Altshuler, David Johansson, Stefan Bjørkhaug, Lise Njølstad, Pål Rasmus Diabetes Metabolism Variants in HNF1A encoding hepatocyte nuclear factor 1α (HNF-1A) are associated with maturity-onset diabetes of the young form 3 (MODY 3) and type 2 diabetes. We investigated whether functional classification of HNF1A rare coding variants can inform models of diabetes risk prediction in the general population by analyzing the effect of 27 HNF1A variants identified in well-phenotyped populations (n = 4,115). Bioinformatics tools classified 11 variants as likely pathogenic and showed no association with diabetes risk (combined minor allele frequency [MAF] 0.22%; odds ratio [OR] 2.02; 95% CI 0.73–5.60; P = 0.18). However, a different set of 11 variants that reduced HNF-1A transcriptional activity to <60% of normal (wild-type) activity was strongly associated with diabetes in the general population (combined MAF 0.22%; OR 5.04; 95% CI 1.99–12.80; P = 0.0007). Our functional investigations indicate that 0.44% of the population carry HNF1A variants that result in a substantially increased risk for developing diabetes. These results suggest that functional characterization of variants within MODY genes may overcome the limitations of bioinformatics tools for the purposes of presymptomatic diabetes risk prediction in the general population. American Diabetes Association 2017-02 2016-11-29 /pmc/articles/PMC5860263/ /pubmed/27899486 http://dx.doi.org/10.2337/db16-0460 Text en © 2017 by the American Diabetes Association. http://www.diabetesjournals.org/content/licenseReaders may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at http://www.diabetesjournals.org/content/license. |
spellingShingle | Metabolism Najmi, Laeya Abdoli Aukrust, Ingvild Flannick, Jason Molnes, Janne Burtt, Noel Molven, Anders Groop, Leif Altshuler, David Johansson, Stefan Bjørkhaug, Lise Njølstad, Pål Rasmus Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population |
title | Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population |
title_full | Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population |
title_fullStr | Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population |
title_full_unstemmed | Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population |
title_short | Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population |
title_sort | functional investigations of hnf1a identify rare variants as risk factors for type 2 diabetes in the general population |
topic | Metabolism |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860263/ https://www.ncbi.nlm.nih.gov/pubmed/27899486 http://dx.doi.org/10.2337/db16-0460 |
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