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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 LU ; Altshuler, David ; Johansson, Stefan and Bjørkhaug, Lise , et al. (2017) In Diabetes 66(2). p.335-346
Abstract

Variants in HNF1A encoding hepatocyte nuclear factor 1a (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... (More)

Variants in HNF1A encoding hepatocyte nuclear factor 1a (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.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Diabetes
volume
66
issue
2
pages
12 pages
publisher
American Diabetes Association Inc.
external identifiers
  • pmid:27899486
  • wos:000392691000012
  • scopus:85011706266
ISSN
0012-1797
DOI
10.2337/db16-0460
language
English
LU publication?
yes
id
ff4cfe1c-261d-4f5d-913d-bb8a646457a7
date added to LUP
2017-02-28 08:23:50
date last changed
2025-03-03 12:55:26
@article{ff4cfe1c-261d-4f5d-913d-bb8a646457a7,
  abstract     = {{<p>Variants in HNF1A encoding hepatocyte nuclear factor 1a (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 &lt;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.</p>}},
  author       = {{Najmi, Laeya Abdoli and Aukrust, Ingvild and Flannick, Jason and Molnes, Janne and Burtt, Noel and Molven, Anders and Groop, Leif and Altshuler, David and Johansson, Stefan and Bjørkhaug, Lise and Njølstad, Pål Rasmus}},
  issn         = {{0012-1797}},
  language     = {{eng}},
  month        = {{02}},
  number       = {{2}},
  pages        = {{335--346}},
  publisher    = {{American Diabetes Association Inc.}},
  series       = {{Diabetes}},
  title        = {{Functional investigations of HNF1A identify rare variants as risk factors for type 2 diabetes in the general population}},
  url          = {{http://dx.doi.org/10.2337/db16-0460}},
  doi          = {{10.2337/db16-0460}},
  volume       = {{66}},
  year         = {{2017}},
}