ArticlePloS one2013
The value of genetic information for diabetes risk prediction - differences according to sex, age, family history and obesity.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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16 citing papers in PubMed, 40 citations in OpenAlex.
- The effect of genetic counseling for adult offspring of patients with type 2 diabetes on attitudes toward diabetes and its heredity: a randomized controlled trial.Journal of genetic counseling · 2014Trial
- Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation.European journal of clinical investigation · 2025Review
- A novel predictive model for optimizing diabetes screening in older adults.Journal of diabetes investigation · 2024Article
- The impact of age on genetic risk for common diseases.PLoS genetics · 2021Article
- A Genetic Risk Score Improves the Prediction of Type 2 Diabetes Mellitus in Mexican Youths but Has Lower Predictive Utility Compared With Non-Genetic Factors.Frontiers in endocrinology · 2021Article
- Age-related late-onset disease heritability patterns and implications for genome-wide association studies.PeerJ · 2019Article
- Article
- Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives.Human genetics · 2016Review
- Genetic diagnosis and prognosis of Alzheimer's disease: challenges and opportunities.Expert review of molecular diagnostics · 2015Review
- Genomic-based tools for the risk assessment, management, and prevention of type 2 diabetes.The application of clinical genetics · 2015Review
- Article
- Susceptibility to type 2 diabetes mellitus--from genes to prevention.Nature reviews. Endocrinology · 2014Review
- Genetic insights into cardiometabolic risk factors.The Clinical biochemist. Reviews · 2014Review
- Genetic-based prediction of disease traits: prediction is very difficult, especially about the future.Frontiers in genetics · 2014Review
- Insights into the genetic susceptibility to type 2 diabetes from genome-wide association studies of glycaemic traits.Current diabetes reports · 2014Review
- Life course health care and preemptive approach to non-communicable diseases.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2013Review
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenome-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.
methodsA case-cohort study (random subcohort N = 1,968; incident cases: N = 578) 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)).
resultsA 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.
conclusionThere 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.
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