Jordi Merino1,2, Miriam S Udler3,4, Aaron Leong1,2,5, James B Meigs2,5. 1. Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02115, USA. 2. Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA. 3. Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02115, USA. mudler@mgh.harvard.edu. 4. Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA. mudler@mgh.harvard.edu. 5. Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
Abstract
PURPOSE OF REVIEW: The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction. RECENT FINDINGS: In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bioinformatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for "multi-omic" prediction to improve health.
PURPOSE OF REVIEW: The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction. RECENT FINDINGS: In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bioinformatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for "multi-omic" prediction to improve health.
Entities:
Keywords:
Genomics; Metabolomics; Risk prediction; T2D comorbidities; Type 2 diabetes
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