Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study.

Diabetes care - 1 Nov 2009

Schulze Matthias B, Weikert Cornelia, Pischon Tobias, Bergmann Manuela M, Al-Hasani Hadi, Schleicher Erwin, Fritsche Andreas, Häring Hans-Ulrich, Boeing Heiner, Joost Hans-Georg

Abstract excerpt

OBJECTIVE: We investigated whether metabolic biomarkers and single nucleotide polymorphisms (SNPs) improve diabetes prediction beyond age, anthropometry, and lifestyle risk factors. RESEARCH DESIGN AND METHODS: A case-cohort study within a prospective study was designed. We randomly selected a subcohort (n = 2,500) from 26,444 participants, of whom 1,962 were diabetes free at baseline. Of the 801 incident type 2...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Alanine Transaminase
Share to Area Under Curve

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Blood Glucose

Share to Cholesterol, HDL

Share to gamma-Glutamyltransferase

Share to Germany

Share to Glycated Hemoglobin

Share to ROC Curve

Source

Open in PubMed Open full text

Identifiers

PMID: 19720844
DOI: 10.2337/dc09-0197
PMCID: PMC2768223

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study.PMID 19720844Read ↗

The value of genetic information for diabetes risk prediction - differences according to sex, age, family history and obesity.Semantic proximity Read ↗

Metabolite traits and genetic risk provide complementary information for the prediction of future type 2 diabetes.Semantic proximity Read ↗

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

Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study.Semantic proximity Read ↗

Quantifying the utility of type 2 diabetes polygenic risk score for predicting incident diabetes: an analysis of large US-based cohort studies.Semantic proximity Read ↗

Biomarkers for type 2 diabetesSemantic proximity Read ↗

Predicting risk of type 2 diabetes mellitus with genetic risk models on the basis of established genome-wide association markers: a systematic review.Semantic proximity Read ↗

Large-scale multi-omics enhance risk prediction for type 2 diabetes.Semantic proximity Read ↗

Associations of Combined Genetic and Lifestyle Risks With Incident Type 2 Diabetes in the UK Biobank.Semantic proximity Read ↗

Identifying type 1 and 2 diabetes in population level data: assessing the accuracy of published approachesSemantic proximity Read ↗

Incorporating polygenic risk into the Leicester Risk Assessment score for 10-year risk prediction of type 2 diabetes.Semantic proximity Read ↗

Biomarkers for predicting type 2 diabetes development—Can metabolomics improve on existing biomarkers?Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.