Open AccessPrecision medicine in diabetes prevention, classification and management
Author(s) -
Xie Fangying,
Chan Juliana CN,
Ma Ronald CW
Publication year - 2018
Publication title -
journal of diabetes investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.089
H-Index - 50
eISSN - 2040-1124
pISSN - 2040-1116
DOI - 10.1111/jdi.12830
Subject(s) - medicine , personalized medicine , precision medicine , diabetes mellitus , diabetes management , prioritization , intensive care medicine , health care , genetic testing , perspective (graphical) , risk analysis (engineering) , bioinformatics , data science , type 2 diabetes , management science , computer science , artificial intelligence , pathology , economic growth , economics , biology , endocrinology
Diabetes has become a major burden of healthcare expenditure. Diabetes management following a uniform treatment algorithm is often associated with progressive treatment failure and development of diabetic complications. Recent advances in our understanding of the genomic architecture of diabetes and its complications have provided the framework for development of precision medicine to personalize diabetes prevention and management. In the present review, we summarized recent advances in the understanding of the genetic basis of diabetes and its complications. From a clinician's perspective, we attempted to provide a balanced perspective on the utility of genomic medicine in the field of diabetes. Using genetic information to guide management of monogenic forms of diabetes represents the best‐known examples of genomic medicine for diabetes. Although major strides have been made in genetic research for diabetes, its complications and pharmacogenetics, ongoing efforts are required to translate these findings into practice by incorporating genetic information into a risk prediction model for prioritization of treatment strategies, as well as using multi‐omic analyses to discover novel drug targets with companion diagnostics. Further research is also required to ensure the appropriate use of this information to empower individuals and healthcare professionals to make personalized decisions for achieving the optimal outcome.