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Identification of putative biomarkers for type 2 diabetes using metabolomics in the Korea Association REsource (KARE) cohort
- Source :
- Metabolomics. 12
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
Abstract
- Type 2 diabetes (T2D) is a multifactorial disease resulting from a complex interaction between environmental and genetic risk factors. Metabolomics provide a logical framework that reflects the functional endpoints of biological processes being triggered by genetic information and various external influences. Identification of metabolite biomarkers can shed insight into etiological pathways and improve the prediction of disease risk. Here, we aimed to identify serum metabolites as putative biomarkers for T2D and their association with genetic variants in the Korean population. A targeted metabolomics approach was employed to quantify serum metabolites for 2240 participants in the Korea Association REsource (KARE) cohort. T2D-related metabolites were identified by statistical methods including multivariable linear and logistic regression, and were independently replicated in the Cooperative Health Research in the Region of Augsburg (KORA) cohort. Additionally, by combining a genome wide association study (GWAS) with metabolomics, genetic variants associated with the identified T2D-related metabolites were uncovered. 123 metabolites were quantified from fasting serum samples and four metabolites, hexadecanoylcarnitine (C16), glycine, lysophosphatidylcholine acyl C18:2 (lysoPC a C18:2), and phosphatidylcholine acyl-alkyl C36:0 (PC ae C36:0), were significantly altered in T2D compared to non-T2D subjects (after the Bonferroni correction for multiple testing with P
- Subjects :
- 0301 basic medicine
endocrine system diseases
Endocrinology, Diabetes and Metabolism
Metabolite
Clinical Biochemistry
030209 endocrinology & metabolism
Genome-wide association study
Type 2 diabetes
Biology
Biochemistry
03 medical and health sciences
chemistry.chemical_compound
symbols.namesake
0302 clinical medicine
Metabolomics
medicine
Genetics
nutritional and metabolic diseases
medicine.disease
030104 developmental biology
Bonferroni correction
chemistry
Multiple comparisons problem
Cohort
symbols
Cohort study
Subjects
Details
- ISSN :
- 15733890 and 15733882
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- Metabolomics
- Accession number :
- edsair.doi...........efe02e6e546a2f1b6fcb020b523a43d4