Daniel Gonzalez Izundegui1, Matthew Nayor2. 1. Department of Medicine, Boston University School of Medicine, Boston, MA, USA. 2. Sections of Cardiology and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA. mnayor@bu.edu.
Abstract
PURPOSE OF REVIEW: Metabolomics enables rapid interrogation of widespread metabolic processes making it well suited for studying diabetes. Here, we review the current status of metabolomic investigation in diabetes, highlighting its applications for improving risk prediction and mechanistic understanding. RECENT FINDINGS: Findings of metabolite associations with type 2 diabetes risk have confirmed experimental observations (e.g., branched-chain amino acids) and also pinpointed novel pathways of diabetes risk (e.g., dimethylguanidino valeric acid). In type 1 diabetes, abnormal metabolite patterns are observed prior to the development of autoantibodies and hyperglycemia. Diabetes complications display specific metabolite signatures that are distinct from the metabolic derangements of diabetes and differ across vascular beds. Lastly, metabolites respond acutely to pharmacologic treatment, providing opportunities to understand inter-individual treatment responses. Metabolomic studies have elucidated biological mechanisms underlying diabetes development, complications, and therapeutic response. While not yet ready for clinical translation, metabolomics is a powerful and promising precision medicine tool.
PURPOSE OF REVIEW: Metabolomics enables rapid interrogation of widespread metabolic processes making it well suited for studying diabetes. Here, we review the current status of metabolomic investigation in diabetes, highlighting its applications for improving risk prediction and mechanistic understanding. RECENT FINDINGS: Findings of metabolite associations with type 2 diabetes risk have confirmed experimental observations (e.g., branched-chain amino acids) and also pinpointed novel pathways of diabetes risk (e.g., dimethylguanidino valeric acid). In type 1 diabetes, abnormal metabolite patterns are observed prior to the development of autoantibodies and hyperglycemia. Diabetes complications display specific metabolite signatures that are distinct from the metabolic derangements of diabetes and differ across vascular beds. Lastly, metabolites respond acutely to pharmacologic treatment, providing opportunities to understand inter-individual treatment responses. Metabolomic studies have elucidated biological mechanisms underlying diabetes development, complications, and therapeutic response. While not yet ready for clinical translation, metabolomics is a powerful and promising precision medicine tool.
Authors: Svati H Shah; James R Bain; Michael J Muehlbauer; Robert D Stevens; David R Crosslin; Carol Haynes; Jennifer Dungan; L Kristin Newby; Elizabeth R Hauser; Geoffrey S Ginsburg; Christopher B Newgard; William E Kraus Journal: Circ Cardiovasc Genet Date: 2010-02-19
Authors: Jeremy M Robbins; Matthew Herzig; Jordan Morningstar; Mark A Sarzynski; Daniel E Cruz; Thomas J Wang; Yan Gao; James G Wilson; Claude Bouchard; Tuomo Rankinen; Robert E Gerszten Journal: JAMA Cardiol Date: 2019-07-01 Impact factor: 14.676
Authors: Ruifang Li-Gao; David A Hughes; Jan B van Klinken; Renée de Mutsert; Frits R Rosendaal; Dennis O Mook-Kanamori; Nicholas J Timpson; Ko Willems van Dijk Journal: Diabetes Date: 2021-10-05 Impact factor: 9.461
Authors: Sean H Adams; Charles L Hoppel; Kerry H Lok; Ling Zhao; Scott W Wong; Paul E Minkler; Daniel H Hwang; John W Newman; W Timothy Garvey Journal: J Nutr Date: 2009-04-15 Impact factor: 4.798
Authors: Lina A Dahabiyeh; Muhammad Mujammami; Tawfiq Arafat; Hicham Benabdelkamel; Assim A Alfadda; Anas M Abdel Rahman Journal: Front Pharmacol Date: 2021-07-15 Impact factor: 5.810
Authors: Ninna H Tougaard; Marie Frimodt-Møller; Hanne Salmenkari; Elisabeth B Stougaard; Andressa D Zawadzki; Ismo M Mattila; Tine W Hansen; Cristina Legido-Quigley; Sohvi Hörkkö; Carol Forsblom; Per-Henrik Groop; Markku Lehto; Peter Rossing Journal: J Clin Med Date: 2022-06-21 Impact factor: 4.964
Authors: Daniel Gonzalez Izundegui; Patricia E Miller; Ravi V Shah; Clary B Clish; Maura E Walker; Gary F Mitchell; Robert E Gerszten; Martin G Larson; Ramachandran S Vasan; Matthew Nayor Journal: Cardiovasc Diabetol Date: 2022-10-15 Impact factor: 8.949