{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Hong EP"],"funding":["Hallym University"],"pagination":["6"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7824099"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["11(1)"],"pubmed_abstract":["Personalized risk prediction for diabetic cardiovascular disease (DCVD) is at the core of precision medicine in type 2 diabetes (T2D). We first identified three marker sets consisting of 15, 47, and 231 tagging single nucleotide polymorphisms (tSNPs) associated with DCVD using a linear mixed model in 2378 T2D patients obtained from four population-based Korean cohorts. Using the genetic variants with even modest effects on phenotypic variance, we observed improved risk stratification accuracy beyond traditional risk factors (AUC, 0.63 to 0.97). With a cutoff point of 0.21, the discrete genetic liability threshold model consisting of 231 SNPs (GLT<sub>231</sub>) correctly classified 87.7% of 2378 T2D patients as high or low risk of DCVD. For the same set of SNP markers, the GLT and polygeni"],"journal":["Metabolites"],"pubmed_title":["The Liability Threshold Model for Predicting the Risk of Cardiovascular Disease in Patients with Type 2 Diabetes: A Multi-Cohort Study of Korean Adults."],"pmcid":["PMC7824099"],"funding_grant_id":["HRF-201711-015"],"pubmed_authors":["Hong EP","Park JW","Heo SG"],"additional_accession":[]},"is_claimable":false,"name":"The Liability Threshold Model for Predicting the Risk of Cardiovascular Disease in Patients with Type 2 Diabetes: A Multi-Cohort Study of Korean Adults.","description":"Personalized risk prediction for diabetic cardiovascular disease (DCVD) is at the core of precision medicine in type 2 diabetes (T2D). We first identified three marker sets consisting of 15, 47, and 231 tagging single nucleotide polymorphisms (tSNPs) associated with DCVD using a linear mixed model in 2378 T2D patients obtained from four population-based Korean cohorts. Using the genetic variants with even modest effects on phenotypic variance, we observed improved risk stratification accuracy beyond traditional risk factors (AUC, 0.63 to 0.97). With a cutoff point of 0.21, the discrete genetic liability threshold model consisting of 231 SNPs (GLT<sub>231</sub>) correctly classified 87.7% of 2378 T2D patients as high or low risk of DCVD. For the same set of SNP markers, the GLT and polygeni","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Dec","modification":"2026-04-29T21:27:26.918Z","creation":"2021-02-21T03:01:30Z"},"accession":"S-EPMC7824099","cross_references":{"pubmed":["33374401"],"doi":["10.3390/metabo11010006"]}}