The value of genetic information for diabetes risk prediction - differences according to sex, age, family history and obesity.
PLoS One
; 8(5): e64307, 2013.
Article
in En
| MEDLINE
| ID: mdl-23700469
ABSTRACT
BACKGROUND:
Genome-wide association studies have identified numerous single nucleotide polymorphisms associated with type 2 diabetes through the past years. In previous studies, the usefulness of these genetic markers for prediction of diabetes was found to be limited. However, differences may exist between substrata of the population according to the presence of major diabetes risk factors. This study aimed to investigate the added predictive value of genetic information (42 single nucleotide polymorphisms) in subgroups of sex, age, family history of diabetes, and obesity.METHODS:
A case-cohort study (random subcohort Nâ=â1,968; incident cases Nâ=â578) within the European Prospective Investigation into Cancer and Nutrition Potsdam study was used. Prediction models without and with genetic information were evaluated in terms of the area under the receiver operating characteristic curve and the integrated discrimination improvement. Stratified analyses included subgroups of sex, age (<50 or ≥50 years), family history (positive if either father or mother or a sibling has/had diabetes), and obesity (BMI< or ≥30 kg/m(2)).RESULTS:
A genetic risk score did not improve prediction above classic and metabolic markers, but - compared to a non-invasive prediction model - genetic information slightly improved the area under the receiver operating characteristic curve (difference [95%-CI] 0.007 [0.002-0.011]). Stratified analyses showed stronger improvement in the older age group (0.010 [0.002-0.018]), the group with a positive family history (0.012 [0.000-0.023]) and among obese participants (0.015 [-0.005-0.034]) compared to the younger participants (0.005 [-0.004-0.014]), participants with a negative family history (0.003 [-0.001-0.008]) and non-obese (0.007 [0.000-0.014]), respectively. No difference was found between men and women.CONCLUSION:
There was no incremental value of genetic information compared to standard non-invasive and metabolic markers. Our study suggests that inclusion of genetic variants in diabetes risk prediction might be useful for subgroups with already manifest risk factors such as older age, a positive family history and obesity.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Diabetes Mellitus, Type 2
/
Obesity
Type of study:
Diagnostic_studies
/
Etiology_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Adult
/
Female
/
Humans
/
Male
/
Middle aged
Language:
En
Journal:
PLoS One
Journal subject:
CIENCIA
/
MEDICINA
Year:
2013
Document type:
Article
Affiliation country:
Germany
Country of publication:
EEUU
/
ESTADOS UNIDOS
/
ESTADOS UNIDOS DA AMERICA
/
EUA
/
UNITED STATES
/
UNITED STATES OF AMERICA
/
US
/
USA