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Evaluating the discriminative power of multi-trait genetic risk scores for type 2 diabetes in a northern Swedish population

Fontaine-Bisson, B.; Renstrom, F.; Rolandsson, O.; Payne, F.; Hallmans, G.; Barroso, I. and Franks, Paul LU (2010) In Diabetologia 53(10). p.2155-2162
Abstract
We determined whether single nucleotide polymorphisms (SNPs) previously associated with diabetogenic traits improve the discriminative power of a type 2 diabetes genetic risk score. Participants (n = 2,751) were genotyped for 73 SNPs previously associated with type 2 diabetes, fasting glucose/insulin concentrations, obesity or lipid levels, from which five genetic risk scores (one for each of the four traits and one combining all SNPs) were computed. Type 2 diabetes patients and non-diabetic controls (n = 1,327/1,424) were identified using medical records in addition to an independent oral glucose tolerance test. Model 1, including only SNPs associated with type 2 diabetes, had a discriminative power of 0.591 (p < 1.00 x 10(-20) vs null... (More)
We determined whether single nucleotide polymorphisms (SNPs) previously associated with diabetogenic traits improve the discriminative power of a type 2 diabetes genetic risk score. Participants (n = 2,751) were genotyped for 73 SNPs previously associated with type 2 diabetes, fasting glucose/insulin concentrations, obesity or lipid levels, from which five genetic risk scores (one for each of the four traits and one combining all SNPs) were computed. Type 2 diabetes patients and non-diabetic controls (n = 1,327/1,424) were identified using medical records in addition to an independent oral glucose tolerance test. Model 1, including only SNPs associated with type 2 diabetes, had a discriminative power of 0.591 (p < 1.00 x 10(-20) vs null model) as estimated by the area under the receiver operator characteristic curve (ROC AUC). Model 2, including only fasting glucose/insulin SNPs, had a significantly higher discriminative power than the null model (ROC AUC 0.543; p = 9.38 x 10(-6) vs null model), but lower discriminative power than model 1 (p = 5.92 x 10(-5)). Model 3, with only lipid-associated SNPs, had significantly higher discriminative power than the null model (ROC AUC 0.565; p = 1.44 x 10(-9)) and was not statistically different from model 1 (p = 0.083). The ROC AUC of model 4, which included only obesity SNPs, was 0.557 (p = 2.30 x 10(-7) vs null model) and smaller than model 1 (p = 0.025). Finally, the model including all SNPs yielded a significant improvement in discriminative power compared with the null model (p < 1.0 x 10(-20)) and model 1 (p = 1.32 x 10(-5)); its ROC AUC was 0.626. Adding SNPs previously associated with fasting glucose, insulin, lipids or obesity to a genetic risk score for type 2 diabetes significantly increases the power to discriminate between people with and without clinically manifest type 2 diabetes compared with a model including only conventional type 2 diabetes loci. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Type 2 diabetes, Predictive power, Polymorphism, Obesity, Lipids, Insulin, Glucose, Discriminative power, Genetic risk score
in
Diabetologia
volume
53
issue
10
pages
2155 - 2162
publisher
Springer Verlag
external identifiers
  • wos:000281612600012
  • scopus:77958027965
ISSN
1432-0428
DOI
10.1007/s00125-010-1792-y
language
English
LU publication?
yes
id
dbb69f85-5914-4c32-9f3e-a08dc6764582 (old id 1697790)
date added to LUP
2010-10-22 14:24:52
date last changed
2018-05-29 11:35:13
@article{dbb69f85-5914-4c32-9f3e-a08dc6764582,
  abstract     = {We determined whether single nucleotide polymorphisms (SNPs) previously associated with diabetogenic traits improve the discriminative power of a type 2 diabetes genetic risk score. Participants (n = 2,751) were genotyped for 73 SNPs previously associated with type 2 diabetes, fasting glucose/insulin concentrations, obesity or lipid levels, from which five genetic risk scores (one for each of the four traits and one combining all SNPs) were computed. Type 2 diabetes patients and non-diabetic controls (n = 1,327/1,424) were identified using medical records in addition to an independent oral glucose tolerance test. Model 1, including only SNPs associated with type 2 diabetes, had a discriminative power of 0.591 (p &lt; 1.00 x 10(-20) vs null model) as estimated by the area under the receiver operator characteristic curve (ROC AUC). Model 2, including only fasting glucose/insulin SNPs, had a significantly higher discriminative power than the null model (ROC AUC 0.543; p = 9.38 x 10(-6) vs null model), but lower discriminative power than model 1 (p = 5.92 x 10(-5)). Model 3, with only lipid-associated SNPs, had significantly higher discriminative power than the null model (ROC AUC 0.565; p = 1.44 x 10(-9)) and was not statistically different from model 1 (p = 0.083). The ROC AUC of model 4, which included only obesity SNPs, was 0.557 (p = 2.30 x 10(-7) vs null model) and smaller than model 1 (p = 0.025). Finally, the model including all SNPs yielded a significant improvement in discriminative power compared with the null model (p &lt; 1.0 x 10(-20)) and model 1 (p = 1.32 x 10(-5)); its ROC AUC was 0.626. Adding SNPs previously associated with fasting glucose, insulin, lipids or obesity to a genetic risk score for type 2 diabetes significantly increases the power to discriminate between people with and without clinically manifest type 2 diabetes compared with a model including only conventional type 2 diabetes loci.},
  author       = {Fontaine-Bisson, B. and Renstrom, F. and Rolandsson, O. and Payne, F. and Hallmans, G. and Barroso, I. and Franks, Paul},
  issn         = {1432-0428},
  keyword      = {Type 2 diabetes,Predictive power,Polymorphism,Obesity,Lipids,Insulin,Glucose,Discriminative power,Genetic risk score},
  language     = {eng},
  number       = {10},
  pages        = {2155--2162},
  publisher    = {Springer Verlag},
  series       = {Diabetologia},
  title        = {Evaluating the discriminative power of multi-trait genetic risk scores for type 2 diabetes in a northern Swedish population},
  url          = {http://dx.doi.org/10.1007/s00125-010-1792-y},
  volume       = {53},
  year         = {2010},
}